Collaborative Appearance-Based Place Recognition And Improving Place Recognition Using Detection Of Dynamic Objects, 2018 The Graduate Center, City University of New York
Collaborative Appearance-Based Place Recognition And Improving Place Recognition Using Detection Of Dynamic Objects, Juan Pablo Munoz
All Dissertations, Theses, and Capstone Projects
This dissertation makes contributions to the problem of Long-Term Appearance-Based Place Recognition. We present a framework for place recognition in a collaborative scheme and a method to reduce the impact of dynamic objects on place representations. We demonstrate our findings using a state-of-the-art place recognition approach.
We begin in Part I by describing the general problem of place recognition and its importance in applications where accurate localization is crucial. We discuss feature detection and description and also explain the functioning of several place recognition frameworks.
In Part II, we present a novel framework for collaboration between agents from a pure ...
Deep Gaze Velocity Analysis During Mammographic Reading For Biometric Identification Of Radiologists, 2018 Biomedical Sciences, Engineering, and Computing Group Health Data Sciences Institute, Oak Ridge National Laboratory
Deep Gaze Velocity Analysis During Mammographic Reading For Biometric Identification Of Radiologists, Hong-Jun Yoon, Folami Alamudun, Kathy Hudson, Garnetta Morin-Ducote, Georgia Tourassi
Journal of Human Performance in Extreme Environments
Several studies have confirmed that the gaze velocity of the human eye can be utilized as a behavioral biometric or personalized biomarker. In this study, we leverage the local feature representation capacity of convolutional neural networks (CNNs) for eye gaze velocity analysis as the basis for biometric identification of radiologists performing breast cancer screening. Using gaze data collected from 10 radiologists reading 100 mammograms of various diagnoses, we compared the performance of a CNN-based classification algorithm with two deep learning classifiers, deep neural network and deep belief network, and a previously presented hidden Markov model classifier. The study showed that ...
Gene Regulatory Network Inference From Perturbed Time-Series Expression Data Via Ordered Dynamical Expansion Of Non-Steady State Actors, Mahdi Zamanighomi, Mostafa Zamanian, Michael J. Kimber, Zhengdao Wang
The reconstruction of gene regulatory networks from gene expression data has been the subject of intense research activity. A variety of models and methods have been developed to address different aspects of this important problem. However, these techniques are narrowly focused on particular biological and experimental platforms, and require experimental data that are typically unavailable and difficult to ascertain. The more recent availability of higher-throughput sequencing platforms, combined with more precise modes of genetic perturbation, presents an opportunity to formulate more robust and comprehensive approaches to gene network inference. Here, we propose a step-wise framework for identifying gene-gene regulatory interactions ...
Joint Optimization Of Power Allocation And Training Duration For Uplink Multiuser Mimo Communications, 2018 Iowa State University
Joint Optimization Of Power Allocation And Training Duration For Uplink Multiuser Mimo Communications, Songtao Lu, Zhengdao Wang
In this paper, we consider a multiuser multiple-input multiple-output (MU-MIMO) communication system between a base station equipped with multiple antennas and multiple mobile users each equipped with a single antenna. The uplink scenario is considered. The uplink channels are acquired by the base station through a training phase. Two linear processing schemes are considered, namely maximum-ratio combining (MRC) and zero-forcing (ZF). We optimize the training period and optimal training energy under the average and peak power constraint so that an achievable sum rate is maximized.
A Nonconvex Splitting Method For Symmetric Nonnegative Matrix Factorization: Convergence Analysis And Optimality, 2018 Iowa State University
A Nonconvex Splitting Method For Symmetric Nonnegative Matrix Factorization: Convergence Analysis And Optimality, Songtao Lu, Mingyi Hong, Zhengdao Wang
Symmetric nonnegative matrix factorization (SymNMF) has important applications in data analytics problems such as document clustering, community detection, and image segmentation. In this paper, we propose a novel nonconvex variable splitting method for solving SymNMF. The proposed algorithm is guaranteed to converge to the set of Karush-Kuhn-Tucker (KKT) points of the nonconvex SymNMF problem. Furthermore, it achieves a global sublinear convergence rate. We also show that the algorithm can be efficiently implemented in parallel. Further, sufficient conditions are provided that guarantee the global and local optimality of the obtained solutions. Extensive numerical results performed on both synthetic and real datasets ...
Many Access For Small Packets Based On Precoding And Sparsity-Aware Recovery, 2018 Chinese Academy of Sciences
Many Access For Small Packets Based On Precoding And Sparsity-Aware Recovery, Ronggui Xie, Huarui Yin, Xiaohui Chen, Zhengdao Wang
Modern mobile terminals produce massive small data packets. For these short-length packets, it is inefficient to follow the current multiple access schemes to allocate transmission resources due to heavy signaling overhead. We propose a non-orthogonal many-access scheme that is well suited for the future communication systems equipped with many receive antennas. The system is modeled as having a block-sparsity pattern with unknown sparsity level (i.e., unknown number of transmitted messages). Block precoding is employed at each single-antenna transmitter to enable the simultaneous transmissions of many users. The number of simultaneously served active users is allowed to be even more ...
Degrees Of Freedom Region Of Wireless X Networks Based On Real Interference Alignment, 2018 Stanford University
Degrees Of Freedom Region Of Wireless X Networks Based On Real Interference Alignment, Mahdi Zamanighomi, Zhengdao Wang
We first consider a single hop wireless X network with K transmitters and J receivers, all with a single antenna. Each transmitter conveys an independent message for each receiver. The channel is assumed to have constant coefficients. We develop an interference alignment scheme for this setup and derive an achievable degrees of freedom (DoF) region. We show that in some cases, the derived region meets a previous outer bound, and hence, is the (exact) DoF region. For our achievability schemes, we divide each message into streams and use real interference alignment on the streams. Several previous results on the DoF ...
Retrospective Data Filter, 2018 Loyola University Chicago
Retrospective Data Filter, Richard J. Prengaman, Robert E. Thurber, Joe Phipps, Ronald I. Greenberg, Wai L. Hom, James F. Jaworski, Guy W. Riffle
In a target detection communication system, apparatus and method for determining the presence of probable targets based on contacts (which can indicate the presence of a target, noise, chatter, or objects not of interest) detected within a predefined position sector or sectors over a specified number of scans. The position of each detected contact, as a contact of interest, is compared with the positions of contacts detected at previous times or scans. Velocity profiles indicate which previous contacts support the likelihood that the contact of interest represents a target having a velocity within a defined band. The likelihood, which can ...
An Iterative Signal Fusion Method For Reconstruction Of Inplane Strain Maps From Strain Measurements By Hybrid Dense Sensor Networks, Mohammadkazem Sadoughi, Austin Downey, Chao Hu, Simon Laflamme
Civil, Construction and Environmental Engineering Conference Presentations and Proceedings
Flexible skin-like membranes have received considerable research interest for the costeffective monitoring of mesoscale (large-scale) structures. The authors have recently proposed a large-area electronic consisting of a soft elastomeric capacitor (SEC) that transduces a structure's change in geometry (i.e. strain) into a measurable change in capacitance. The SEC sensor measures the summation of the orthogonal strain (i.e. εx + εy). It follows that an algorithm is required for the decomposition of the signal into unidirectional strain maps. In this study, a new method enabling such decomposition that leverages a dense sensor network of SECs and resistive strain gauges ...
Underwater Acoustic Signal Analysis Toolkit, 2017 University of New Orleans, New Orleans
Underwater Acoustic Signal Analysis Toolkit, Kirk Bienvenu Jr
University of 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 ...
Tiled Time Delay Estimation In Mobile Cloud Computing Environments, 2017 Dublin Institute of Technology
Tiled Time Delay Estimation In Mobile Cloud Computing Environments, Ruairí De Fréin
We present a tiled delay estimation technique in the context of Mobile Cloud Computing (MCC) environments. We examine its accuracy in the presence of multiple sources for (1) sub-sample delays and also (2) in the presence of phase-wrap around. Phase wrap-around is prevalent in MCC because the separation of acoustic sources may be large. We show that tiling a histogram of instantaneous phase estimates can improve delay estimates when phase-wrap around is sig- nificantly present and also when multiple sources are present. We report that error in the delay estimator is generally less than 5% of a sample, when the ...
Dual Method Headphone Amplifier, 2017 California Polytechnic State University, San Luis Obispo
Dual Method Headphone Amplifier, Timothy P. Murphy, Joseph S. Gross
Many high impedance headphones underperform their full potential when directly connected to the audio source. Amplifiers boost the audio signal and provide the headphones with sufficient power to ensure their maximum performance. The invention of transistors caused vacuum tube implementation to decline, leaving many audiophiles unsatisfied with the transistor’s sound signature. Vacuum tubes and transistors both amplify signals, however the distinct “tube sound” has vanished.
We have designed and created a product where the user selectively switches between solid-state transistor and tube amplification to compare the sound signatures of each amplification method. The ability to switch between the solid-state ...
Semi-Supervised Convolutional Neural Networks For Human Activity Recognition, 2017 Selected Works
Semi-Supervised Convolutional Neural Networks For Human Activity Recognition, Ming Zeng, Tong Yu, Xiao Wang, Le T. Nguyen, Ole J. Mengshoel, Ian Lane
Ole J Mengshoel
Realtime Implementation Of An Internal-Model-Principle Signal Identifier, 2017 The University of Western Ontario
Realtime Implementation Of An Internal-Model-Principle Signal Identifier, Edris Saleh Mohsen
Electronic Thesis and Dissertation Repository
This thesis presents a new means approach of tuning an adaptive internal model principle based signal identification algorithm whose computational costs are low enough to allow a realtime implementation. The algorithm allows an instantaneous Fourier decomposition of nonstationary signals that have a strongly predictable component. The algorithm is implemented as a feedback loop resulting in a closed loop system with a frequency response of a bandpass filter with notches at the frequencies of the Fourier decomposition. This is achieved through real time selection of the coefficients of the transfer functions in the feedback loop. Previous work showed how the dynamics ...
Feasibility Of 802.11a-Based Transceivers For Vhf/Uhf Communications In Remote Regions, Abhimanyu Nath
Graduate Theses & Non-Theses
The project focuses on adapting a traditional IEEE802.11a specification originally designed for indoors, to work across mountainous terrains such as areas of rural Montana in the UHF band. The goal of the project is to experiment with various CSMA/CA timing parameters to accommodate long propagation delays between mountain peaks. The simulation tool was built in C++. When links with various data rates and hidden nodes were introduced during worst case performance analysis, severe packet drops and queue latencies were found in the network statistics. A few timing optimizations were explored and alternatives were considered in the systems design ...
Design Of Dc-Link Vscf Ac Electrical Power System For The Embraer 190/195 Aircraft, 2017 ETEP – Faculdade de Tecnologia de São José dos Campos, Brazil
Design Of Dc-Link Vscf Ac Electrical Power System For The Embraer 190/195 Aircraft, Eduardo Francis Carvalho Freitas, Nihad E. Daidzic
Journal of Aviation Technology and Engineering
A proposed novel DC-Link VSCF AC-DC-AC electrical power system converter for Embraer 190/195 transport category airplane is presented. The proposed converter could replace the existing conventional system based on the CSCF IDGs. Several contemporary production airplanes already have VSCF as a major or backup source of electrical power. Problems existed with the older VSCF systems in the past; however, the switched power electronics and digital controllers have matured and can be now, in our opinion, safely integrated and replace existing constant-speed hydraulic transmissions powering CSCF AC generators. IGBT power transistors for medium-level power conversion and relatively fast efficient switching ...
On Dual-Band Amplifications Using Dual Two-Tones: Clarifications And Discussion, 2017 Portland State University
On Dual-Band Amplifications Using Dual Two-Tones: Clarifications And Discussion, Siyuan Yan, Xianzhen Yang, Xiao Li, Fu Li
Electrical and Computer Engineering Faculty Publications and Presentations
A significant development of recent research in nonlinear distortion is the expansion of the conventional two-tone test for power amplifiers to the concurrent dual-band transmitters, by Amin et al. A general framework using dual two-tones is developed, which shows that the output signal is affected not only by intermodulation (IM) products but also by cross-modulation (CM) products. In this paper, we will make a number of clarifications to Amin et al.'s paper. The effects of IM and CM in passband will be discussed, IM represents a reduction for compressive devices, and CM reflects an interference caused by the signal ...
Design And Validation Of A Low Cost High Speed Atomic Force Microscope, 2017 Minnesota State University, Mankato
Design And Validation Of A Low Cost High Speed Atomic Force Microscope, Michael Ganzer, Tien Pham
Journal of Undergraduate Research at Minnesota State University, Mankato
The Atomic Force Microscope (AFM) is an important instrument in nanoscale topography, but it is expensive and slow. The authors designed an AFM to overcome both limitations. To do this, they used an Optical Pickup Unit (OPU) from a DVD player as the laser and photodetector system to minimize cost and they did not implement a vertical control loop, which maximized potential speed. Students will be able to be use this device to make nanoscale measurements and engage in micro-engineering. To prototype this idea, the authors tested an OPU with a silicon wafer and demonstrated the ability to consistently distinguish ...
Algorithm For Damage Detection In Wind Turbine Blades Using A Hybrid Dense Sensor Network With Feature Level Data Fusion, Austin Downey, Filippo Ubertini, Simon Laflamme
Civil, Construction and Environmental Engineering Publications
Damage detection in wind turbine blades requires the ability to distinguish local faults over a global area. The implementation of dense sensor networks provides a solution to this local-global monitoring challenge. Here the authors propose a hybrid dense sensor network consisting of capacitive-based thin-film sensors for monitoring the additive strain over large areas and fiber Bragg grating sensors for enforcing boundary conditions. This hybrid dense sensor network is leveraged to derive a data-driven damage detection and localization method for wind turbine blades. In the proposed method, the blade's complex geometry is divided into less geometrically complex sections. Orthogonal strain ...
Separation Of Vocal And Non-Vocal Components From Audio Clip Using Correlated Repeated Mask (Crm), 2017 University of New Orleans
Separation Of Vocal And Non-Vocal Components From Audio Clip Using Correlated Repeated Mask (Crm), Mohan Kumar Kanuri
University of New Orleans Theses and Dissertations
Extraction of singing voice from music is one of the ongoing research topics in the field of speech recognition and audio analysis. In particular, this topic finds many applications in the music field, such as in determining music structure, lyrics recognition, and singer recognition. Although many studies have been conducted for the separation of voice from the background, there has been less study on singing voice in particular.
In this study, efforts were made to design a new methodology to improve the separation of vocal and non-vocal components in audio clips using REPET . In the newly designed method, we ...