Computer Engineering Commons^™

From E-911 To Ng-911: Overview And Challenges In Ecuador, Danilo Corral-De-Witt, Enrique V. Carrera, Jose A. Matamoros-Vargas, Sergio Munoz-Romero, Jose Luis Rojo-Alvarez, Kemal Tepe

Department of Electrical and Computer Engineering: Faculty Publications

For years, emergency attendance institutions in Ecuador worked separately and not all of them had a 24/7 service, resulting in duplicated efforts, a waste of the scarce resources, and an absence of generalized technology. In 2012, Ecuador created an Integrated Security Service, called ECU 911, to address the need of an emergency service articulating all the first response institutions. The ECU 911 relies on the Enhanced 911 technology, having a countrywide presence. Since then, Ecuador has implemented 16 public-safety answering points and 11 decentralized operative rooms, covering all Ecuadorian territory and serving to a population of about 17 million people. …

Obtaining Chemical Selectivity From A Single, Nonselective Sensing Film: Two-Stage Adaptive Estimation Scheme With Multiparameter Measurement To Quantify Mixture Components And Interferents, Karthick Sothivelr, Florian Bender, Fabien Josse Phd, Edwin E. Yaz, Antonio J. Ricco

Electrical and Computer Engineering Faculty Research and Publications

A new approach is reported to detect and quantify the members of a group of small-aromatic-molecule target analytes: benzene, toluene, ethylbenzene, and xylenes (BTEX), dissolved in water, in the presence of interferents, using only the data collected from a single polymer-coated SH-SAW (shear horizontal surface acoustic wave) device and a two-stage adaptive estimation scheme. This technique is composed of exponentially weighted recursive least-squares estimation (EW-RLSE) and a bank of Kalman filters (BKFs) and does not require any prior knowledge of the initial concentration range of the target analytes. The proposed approach utilizes the transient sensor response to sorption and/or desorption …

Chaos Firefly Algorithm With Self-Adaptation Mutation Mechanism For Solving Large-Scale Economic Dispatch With Valve-Point Effects And Multiple Fuel Options, Yude Yang, Bori Wei, Hui Liu, Yiyi Zhang, Junhui Zhao, Emad Manla

Electrical & Computer Engineering and Computer Science Faculty Publications

This paper presents a new metaheuristic optimization algorithm, the firefly algorithm (FA), and an enhanced version of it, called chaos mutation FA (CMFA), for solving power economic dispatch problems while considering various power constraints, such as valve-point effects, ramp rate limits, prohibited operating zones, and multiple generator fuel options. The algorithm is enhanced by adding a new mutation strategy using self-adaptation parameter selection while replacing the parameters with fixed values. The proposed algorithm is also enhanced by a self-adaptation mechanism that avoids challenges associated with tuning the algorithm parameters directed against characteristics of the optimization problem to be solved. The …

Stator Resistance Estimation Using Adaptive Estimation Via A Bank Of Kalman Filters, Alia R. Strandt, Andrew Strandt, Susan C. Schneider, Edwin E. Yaz

Electrical and Computer Engineering Faculty Research and Publications

Accurate and efficient control of electric motors is dependent on knowledge of motor parameters such as the resistance and the inductance of the winding. However, these parameters are often unavailable to the control designer because they are dependent on the motor design and may change due to environmental effects such as temperature. An accurate real-time method to determine the values of these unknown parameters can improve motor performance over the entire operating range. In this work, a parameter estimation technique based on a bank of Kalman filters is used to adaptively estimate the motor winding resistance. Simulation results for a …

Coupled State-Dependent Riccati Equation Control For Continuous Time Nonlinear Mechatronics Systems, Xin Wang, Edwin E. Yaz, Susan C. Schneider

Electrical and Computer Engineering Faculty Research and Publications

This manuscript considers the coupled state-dependent Riccati equation approach for systematically designing nonlinear quadratic regulator and H _∞ control of mechatronics systems. The state-dependent feedback control solutions can be obtained by solving a pair of coupled state-dependent Riccati equations, guaranteeing nonlinear quadratic optimality with inherent stability property in combination with robust ℓ ₂ type of disturbance reduction. The derivation of this control strategy is based on Nash's game theory. Both of finite and infinite horizon control problems are discussed. An underactuated robotic system, Furuta rotary pendulum, is used to examine the effectiveness and robustness of this novel nonlinear control approach.

Dissipative Resilient Observer, M. Sami Fadali, Edwin E. Yaz

Electrical and Computer Engineering Faculty Research and Publications

Cybersecurity is a major concern for designers of control systems that can be directed against any of their components. Observers are an integral part of control systems that require state feedback. This paper considers an observer subject to errors in implementation or subject to cyberattacks. The errors and cyberattacks result in perturbations in the gain and in a finite-energy but unknown disturbance input. We obtain conditions for Q-S-R dissipativity and stability of the observer in the presence of the gain errors and disturbances in the form of linear matrix inequalities (LMIs). Three examples are presented to show how the LMIs …

Development Of Boron Calibration Via Hybrid Comparator Method In Prompt Gamma Activation Analysis, E. J. Artnak, S. R. Biegalski, S. Landsberger, Natale Lanno, Dennis Alexander, M. F. Byers

Department of Electrical and Computer Engineering: Faculty Publications

The prompt gamma activation analysis (PGAA) facility at the Nuclear Engineering Teaching Laboratory at The University of Texas at Austin was utilized to quantify boron concentrations in boron carbide semiconductor films deposited on silicon substrates. Calibration was complicated by the unique and varying sample geometries analyzed. In addition, there was a dearth of solid materials available with quantified boron concentrations having comparable or readily modifiable dimensions to exploit for calibration purposes. Therefore, a novel hybrid comparator method was developed for the quantification of boron utilizing aluminum as an inexpensive and easily machinable reference material. Aluminum samples were manufactured with high …

Combined Use Of Oscillating Means And Ellipsometry To Determine Uncorrelated Effective Thickness And Optical Constants Of Material Deposited At Or Etched From A Working Electrode That Preferrably Comprises Non - Normal Oriented Nanofibers, Mathias M. Schubert, Tino Hofmann, John A. Woollam, Rebecca Y. Lai

Department of Electrical and Computer Engineering: Faculty Publications

Disclosed are systems and methods that enable determination of uncorrelated thickness of a working electrode and surface region optical constants in settings involving electrochemical processing at a working electrodes in a Piezo electric Balance system , by simultaneous application of an Ellipsometer system , the working electrode optionally having a multiplicity of nanofibers that are oriented non normally to a surface of said working electrode . Further disclosed is , simultaneous with said determinations , the monitoring of electrochemical processes at a piezoelectric balance working electrode driven by electrical energy applied between said working electrode and counter electrode .

Forensic Analysis Of Immersive Virtual Reality Social Applications: A Primary Account, Ananya Yarramreddy, Peter Gromkowski, Ibrahim Baggili

Electrical & Computer Engineering and Computer Science Faculty Publications

Our work presents the primary account for exploring the forensics of immersive Virtual Reality (VR) systems and their social applications. The Social VR applications studied in this work include Bigscreen, Altspace VR, Rec Room and Facebook Spaces. We explored the two most widely adopted consumer VR systems: the HTC Vive and the Oculus Rift. Our tests examined the efficacy of reconstructing evidence from network traffic as well as the systems themselves. The results showed that a significant amount of forensically relevant data such as user names, user profile pictures, events, and system details may be recovered. We anticipate that this …

Prior Day Effect In Forecasting Daily Natural Gas Flow From Monthly Data, Maral Fakoor, George F. Corliss, Ronald H. Brown

Electrical and Computer Engineering Faculty Research and Publications

Many needs exist in the energy industry where measurement is monthly yet daily values are required. The process of disaggregation of low frequency measurement to higher frequency values has been presented in this literature. Also, a novel method that accounts for prior-day weather impacts in the disaggregation process is presented, even though prior-day impacts are not directly recoverable from monthly data. Having initial daily weather and gas flow data, the weather and flow data are aggregated to generate simulated monthly weather and consumption data. Linear regression models can be powerful tools for parametrization of monthly/daily consumption models and will enable …

Apple Flower Detection Using Deep Convolutional Networks, Philipe A. Dias, Amy Tabb, Henry P. Medeiros

Electrical and Computer Engineering Faculty Research and Publications

To optimize fruit production, a portion of the flowers and fruitlets of apple trees must be removed early in the growing season. The proportion to be removed is determined by the bloom intensity, i.e., the number of flowers present in the orchard. Several automated computer vision systems have been proposed to estimate bloom intensity, but their overall performance is still far from satisfactory even in relatively controlled environments. With the goal of devising a technique for flower identification which is robust to clutter and to changes in illumination, this paper presents a method in which a pre-trained convolutional neural network …

Grasp And Stress Analysis Of An Underactuated Finger For Proprioceptive Tactile Sensing, Mahyar Abdeetedal, Mehrdad Kermani Ph.D., P.Eng.

Electrical and Computer Engineering Publications

This paper presents the design and evaluation of a new sensorized underactuated self-adaptive finger. The design incorporates a two-degrees-of-freedom link-driven underactuated mechanism with an embedded load cell for contact force measurement and a trimmer potentiometer for acquiring joint variables. The utilization of proprioceptive (internal) sensors results in tactile-like sensations in the finger without compromising the size and complexity of the proposed design. To obtain an optimum finger design, the placement of the load cell is analyzed using finite element method. The design of the finger features a particular rounded shape of the distal phalanx and specific size ratio between the …

Machine Learning For Internet Of Things Data Analysis: A Survey, Mohammad Saeid Mahdavinejad, Mohammadreza Rezvan, Mohammadamin Barekatain, Peyman Adibi, Payam Barnaghi, Amit Sheth

Publications

Rapid developments in hardware, software, and communication technologies have facilitated the emergence of Internet-connected sensory devices that provide observations and data measurements from the physical world. By 2020, it is estimated that the total number of Internet-connected devices being used will be between 25 and 50 billion. As these numbers grow and technologies become more mature, the volume of data being published will increase. The technology of Internet-connected devices, referred to as Internet of Things (IoT), continues to extend the current Internet by providing connectivity and interactions between the physical and cyber worlds. In addition to an increased volume, the …

A Practical Incremental Learning Framework For Sparse Entity Extraction, Hussein Al-Olimat, Steven Gustafson, Jason Mackay, Krishnaprasad Thirunarayan, Amit Sheth

Publications

This work addresses challenges arising from extracting entities from textual data, including the high cost of data annotation, model accuracy, selecting appropriate evaluation criteria, and the overall quality of annotation. We present a framework that integrates Entity Set Expansion (ESE) and Active Learning (AL) to reduce the annotation cost of sparse data and provide an online evaluation method as feedback. This incremental and interactive learning framework allows for rapid annotation and subsequent extraction of sparse data while maintaining high accuracy. We evaluate our framework on three publicly available datasets and show that it drastically reduces the cost of sparse entity …

Micron/Nano Structure Creation Through Dual Pulse Femtosecond Laser Surface Processing, Nicholas Roth

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

A new technique has been developed for creating multiscale micro/nanoscale surfaces on metals. This technique is based on past work in femtosecond laser surface processing (FLSP) and dual pulse laser induced breakdown spectroscopy (LIBS). Using a femtosecond laser, pulse pairs were created with varying pulse separations between 0 ps to 500 ps. The creation of surface structures with dual pulse FLSP was studied on Ag, Cu, Ti, Al, Ni, and 304 stainless steel in relation to pulse separation.

Using dual pulse FLSP micro/nano structures have been created for the first time on silver. The silver structures are multiscale in nature …

Cmos Radioactive Isotope Identification With Multichannel Analyzer And Embedded Neural Network, Samuel Murray

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

A radiation detection and identification system is designed and implemented to perform gamma ray spectroscopy on radioactive sources and identify which isotopes are present in the sources. A multichannel analyzer is implemented on an ASIC to process the signal produced from gamma rays detected by a scintillator and photomultiplier tube and to quantize the gamma ray energies to build a histogram. A fast, low memory embedded neural network is implemented on a microcontroller ASIC to identify the isotopes present in the gamma ray histogram produced by the multichannel analyzer in real time.

Advisors: Sina Balkir and Michael Hoffman

Advanced Recurrent Network-Based Hybrid Acoustic Models For Low Resource Speech Recognition, Jian Kang, Wei-Qiang Zhang, Wei-Wei Liu, Jia Liu, Michael T. Johnson

Electrical and Computer Engineering Faculty Publications

Recurrent neural networks (RNNs) have shown an ability to model temporal dependencies. However, the problem of exploding or vanishing gradients has limited their application. In recent years, long short-term memory RNNs (LSTM RNNs) have been proposed to solve this problem and have achieved excellent results. Bidirectional LSTM (BLSTM), which uses both preceding and following context, has shown particularly good performance. However, the computational requirements of BLSTM approaches are quite heavy, even when implemented efficiently with GPU-based high performance computers. In addition, because the output of LSTM units is bounded, there is often still a vanishing gradient issue over multiple layers. …

Tunable Plasmonic Resonances In Highly Porous Nano-Bamboo Si-Au Superlattice-Type Thin Films, Ufuk Kılıç, Alyssa Mock, René Feder, Derek Sekora, Matthew J. Hilfiker, Rafal Korlacki, Eva Schubert, Christos Argyropoulos, Mathias Schubert

Department of Electrical and Computer Engineering: Faculty Publications

We report on fabrication of spatially-coherent columnar plasmonic nanostructure superlattice-type thin films with high porosity and strong optical anisotropy using glancing angle deposition. Subsequent and repeated depositions of silicon and gold lead to nanometer-dimension subcolumns with controlled lengths. The superlattice-type columns resemble bamboo structures where smaller column sections of gold form junctions sandwiched between larger silicon column sections (“nano-bamboo”). We perform generalized spectroscopic ellipsometry measurements and finite element method computations to elucidate the strongly anisotropic optical properties of the highly-porous nano-bamboo structures. The occurrence of a strongly localized plasmonic mode with displacement pattern reminiscent of a dark quadrupole mode is …

Compact Hardware Implementation Of A Sha-3 Core For Wireless Body Sensor Networks, Yi Yang, Debiao He, Neeraj Kumar, Sherali Zeadally

Information Science Faculty Publications

One of the most important Internet of Things applications is the wireless body sensor network (WBSN), which can provide universal health care, disease prevention, and control. Due to large deployments of small scale smart sensors in WBSNs, security, and privacy guarantees (e.g., security and safety-critical data, sensitive private information) are becoming a challenging issue because these sensor nodes communicate using an open channel, i.e., Internet. We implement data integrity (to resist against malicious tampering) using the secure hash algorithm 3 (SHA-3) when smart sensors in WBSNs communicate with each other using the Internet. Due to the limited resources (i.e., storage, …

Survey Results On Adults And Cybersecurity Education, Frank Breitinger, Joseph Ricci, Ibrahim Baggili

Electrical & Computer Engineering and Computer Science Faculty Publications

Cyberattacks and identity theft are common problems nowadays where researchers often say that humans are the weakest link in the security chain. Therefore, this survey focused on analyzing the interest for adults for ‘cyber threat education seminars’, e.g., how to project themselves and their loved ones. Specifically, we asked questions to understand a possible audience, willingness for paying / time commitment, or fields of interest as well as background and previous training experience. The survey was conducted in late 2016 and taken by 233 participants. The results show that many are worried about cyber threats and about their children exploring …

Adaptive Virtual Impedance Droop Control Based On Consensus Control Of Reactive Current, Zhilin Lu, Qing Wei, Yiyi Zhang, Junhui Zhao, Emad Manla

Electrical & Computer Engineering and Computer Science Faculty Publications

It is difficult to achieve accurate distribution of reactive power based on conventional droop control due to the line impedance mismatch in an islanded microgrid. An adaptive virtual impendence method based on consensus control of reactive current is proposed in this paper. A distributed control structure without the central controller has been established. In this structure, each distributed generation unit (DG) is an independent agent, one-way communication is used between the adjacent DGs, and the reactive power sharing is equivalent to a problem of reactive power current consensus. It has been proven that the system is asymptotically stable under the …

Experience Constructing The Artifact Genome Project (Agp): Managing The Domain's Knowledge One Artifact At A Time, Cinthya Grajeda, Laura Sanchez, Ibrahim Baggili, Devon R. Clark, Frank Breitinger

Electrical & Computer Engineering and Computer Science Faculty Publications

While various tools have been created to assist the digital forensics community with acquiring, processing, and organizing evidence and indicating the existence of artifacts, very few attempts have been made to establish a centralized system for archiving artifacts. The Artifact Genome Project (AGP) has aimed to create the largest vetted and freely available digital forensics repository for Curated Forensic Artifacts (CuFAs). This paper details the experience of building, implementing, and maintaining such a system by sharing design decisions, lessons learned, and future work. We also discuss the impact of AGP in both the professional and academic realms of digital forensics. …

Grasp Synthesis For Purposeful Fracturing Of Object, Mahyar Abdeetedal, Mehrdad Kermani Ph.D., P.Eng.

Electrical and Computer Engineering Publications

No abstract provided.

A Neuromorphic Quadratic, Integrate, And Fire Silicon Neuron With Adaptive Gain, David Parent, Eric Basham

Faculty Publications

An integrated circuit implementation of a silicon neuron was designed, manufactured, and tested. The circuit was designed using the Quadratic, Integrate, and Fire (QIF) neuron model in 0.5 µm silicon technology. The neuron implementation was optimized for low current consumption, drawing only 1.56 mA per QIF circuit and utilized hysteretic reset, non-inverting integrator, and voltage-squarer circuits. The final area of each circuit in silicon was 268 µm height × 400 µm width. This design is the first IC of its kind for this neuron model and is successfully able to output true spiking that follows the behaviors of bistability, monotonic, …

Implementation Of Vision Processing Tasks On A Smart Camera Platform Using Neighborhood Processors, Dingyi Hong

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Two applications of vision processing on a smart camera platform using neighborhood processors are presented. A smart camera application of real-time trajectory calculation for tracking objects and predicting their path of motion by using a single intelligent camera or a dual camera system are designed, simulated and implemented. Another application of object recognition with a key points algorithm for detecting simple shaped objects and locating the camera position within a 3-D coordinate system via imaging by using artificial neural network is applied to provide quick and accurate processing on a neighborhood-level parallel processor or other limited vision chip. For all …

Multiuser Coding And Signal Processing In A Low Power Sensor Network, Dongqi Lai

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Backscatter communication system is a wireless communication system that is used by both academic community and industry circles in recent years. This communication system only requires ultra-low power usage and simple design of the sensors. This project is using backscatter communication system to transmit data with backscatter tags. The method we used is semi-passive backscatter communication. This project focuses on transmitting signals with multiple sensors so there is a problem about distinguishing the signal reflected by different nodes. We modulated the transmitting digital signal with Walsh function to solve the problem of separating the signals between different nodes. By using …

Multiple-Change-Point Modeling And Exact Bayesian Inference Of Degradation Signal For Prognostic Improvement, Yuxin Wen, Jianguo Wu, Qiang Matthew Zhou, Tzu-Liang Bill Tseng

Engineering Faculty Articles and Research

Prognostics play an increasingly important role in modern engineering systems for smart maintenance decision-making. In parametric regression-based approaches, the parametric models are often too rigid to model degradation signals in many applications. In this paper, we propose a Bayesian multiple-change-point (CP) modeling framework to better capture the degradation path and improve the prognostics. At the offline modeling stage, a novel stochastic process is proposed to model the joint prior of CPs and positions. All hyperparameters are estimated through an empirical two-stage process. At the online monitoring and remaining useful life (RUL) prediction stage, a recursive updating algorithm is developed to …

Foreword Special Section On Electrical Contacts, Ronald A. Coutu Jr., Ravi Mahajan

Electrical and Computer Engineering Faculty Research and Publications

Welcome to the Special Topics Section dedicated to the 2016 Holm Conference on Electrical Contacts. This special section contains eight high-quality papers that comprehensively describe the state of the art and potential future directions for topics of great interest to our readers. The Editor-in-Chief (EIC), in consultation with the other EICs, Associate Editors (AEs), and domain experts, selects the topics for the special sections, and a Guest Editor or AE (GE/AE), who is a leading expert in the technical area, then directs the solicitation and peer review of the papers. In cases where the GE/AE is also an author, the …

Rotation Of Two-Petal Laser Beams In The Near Field Of A Spiral Microaxicon, S. S. Stafeev, Liam O'Faolain, M. V. Kotlyar

Cappa Publications

Using a spiral microaxicon with the topological charge 2 and NA = 0.6 operating at a 532-nm wavelength and fabricated by electron-beam lithography, we experimentally demonstrate the rotation of a two-petal laser beam in the near field (several micrometers away from the axicon surface). The estimated rotation rate is 55 °/mm and linearly dependent on the on-axis distance, with the theoretical rotation rate being 53 °/mm. The experimentally measured rotation rate is found to be linear and coincident with the simulation results only on the on-axis segment from 1.5 to 3 mm. The experimentally measured rotation rate is 66 °/mm …

Performance Comparison Of Phase Change Materials And Metal-Insulator Transition Materials For Direct Current And Radio Frequency Switching Applications, Protap Mahanta, Mohiuddin Munna, Ronald A. Coutu Jr.

Electrical and Computer Engineering Faculty Research and Publications

Advanced understanding of the physics makes phase change materials (PCM) and metal-insulator transition (MIT) materials great candidates for direct current (DC) and radio frequency (RF) switching applications. In the literature, germanium telluride (GeTe), a PCM, and vanadium dioxide (VO₂), an MIT material have been widely investigated for DC and RF switching applications due to their remarkable contrast in their OFF/ON state resistivity values. In this review, innovations in design, fabrication, and characterization associated with these PCM and MIT material-based RF switches, have been highlighted and critically reviewed from the early stage to the most recent works. We initially …