Computer Engineering Commons^™

An Electron‐Rich Calix[4]Arene‐Based Receptor With Unprecedented Binding Affinity For Nitric Oxide, Denan Wang, Lena V. Ivanova, Maxim V. Ivanov, Saber Mirzaei, Qadir K. Timerghazin, Scott A. Reid, Rajendra Rathore

Electrical and Computer Engineering Faculty Research and Publications

Calixarenes have found widespread application as building blocks for the design and synthesis of functional materials in host–guest chemistry. The ongoing desire to develop a detailed understanding of the nature of NO bonding to multichromophoric π‐stacked assemblies led us to develop an electron‐rich methoxy derivative of calix[4]arene (3), which we show exists as a single conformer in solution at ambient temperature. Here, we examine the redox properties of this derivative, generate its cation radical (3^+.) using robust chemical oxidants, and determine the relative efficacy of its NO binding in comparison with model calixarenes. We find …

Field Oriented Sliding Mode Control Of Surface-Mounted Permanent Magnet Ac Motors: Theory And Applications To Electrified Vehicles, Xin Wang, Max Reitz, Edwin E. Yaz

Electrical and Computer Engineering Faculty Research and Publications

Permanent magnet ac motors have been extensively utilized for adjustable-speed traction motor drives, due to their inherent advantages including higher power density, superior efficiency and reliability, more precise and rapid torque control, larger power factor, longer bearing, and insulation life-time. Without any proportional-and-integral (PI) controllers, this paper introduces novel first- and higher-order field-oriented sliding mode control schemes. Compared with the traditional PI-based vector control techniques, it is shown that the proposed field oriented sliding mode control methods improve the dynamic torque and speed response, and enhance the robustness to parameter variations, modeling uncertainties, and external load perturbations. While both first- …

Impacts Of Operators’ Behavior On Reliability Of Power Grids During Cascading Failures, Zhuoyao Wang, Mahshid Rahnamay-Naeini, Joana M. Abreu, Rezoan A. Shuvro, Pankaz Das, Andrea Mammoli, Nasir Ghani, Majeed M. Hayat

Electrical and Computer Engineering Faculty Research and Publications

Human operators play a key role in the reliable operation of critical infrastructures. However, human operators may take actions that are far from optimum. This can be due to various factors affecting the operators' performance in time-sensitive and critical situations such as reacting to contingencies with significant monetary and social impacts. In this paper, an analytic framework is proposed based on Markov chains for modeling the dynamics of cascading failures in power grids. The model captures the effects of operators' behavior quantified by the probability of human error under various circumstances. In particular, the observations from historical data and information …

Multispecies Fruit Flower Detection Using A Refined Semantic Segmentation Network, Philipe A. Dias, Amy Tabb, Henry P. Medeiros

Electrical and Computer Engineering Faculty Research and Publications

In fruit production, critical crop management decisions are guided by bloom intensity, i.e., the number of flowers present in an orchard. Despite its importance, bloom intensity is still typically estimated by means of human visual inspection. Existing automated computer vision systems for flower identification are based on hand-engineered techniques that work only under specific conditions and with limited performance. This letter proposes an automated technique for flower identification that is robust to uncontrolled environments and applicable to different flower species. Our method relies on an end-to-end residual convolutional neural network (CNN) that represents the state-of-the-art in semantic segmentation. To enhance …

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 …

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 …

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 …

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 …

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 …

Automatic Segmentation Of Trees In Dynamic Outdoor Environments, Amy Tabb, Henry P. Medeiros

Electrical and Computer Engineering Faculty Research and Publications

Segmentation in dynamic outdoor environments can be difficult when the illumination levels and other aspects of the scene cannot be controlled. Specifically in orchard and vineyard automation contexts, a background material is often used to shield a camera's field of view from other rows of crops. In this paper, we describe a method that uses superpixels to determine low texture regions of the image that correspond to the background material, and then show how this information can be integrated with the color distribution of the image to compute optimal segmentation parameters to segment objects of interest. Quantitative and qualitative experiments …

Do Nir Spectra Collected From Laboratory-Reared Mosquitoes Differ From Those Collected From Wild Mosquitoes?, Masabho Peter Milali, Maggy T. Sikulu-Lord, Samson Sifael Kiware, Floyd E. Dowell, Richard J. Povinelli, George F. Corliss

Electrical and Computer Engineering Faculty Research and Publications

Background

Near infrared spectroscopy (NIRS) is a high throughput technique that measures absorbance of specific wavelengths of light by biological samples and uses this information to classify the age of lab-reared mosquitoes as younger or older than seven days with an average accuracy greater than 80%. For NIRS to estimate ages of wild mosquitoes, a sample of wild mosquitoes with known age in days would be required to train and test the model. Mark-release-recapture is the most reliable method to produce wild-caught mosquitoes of known age in days. However, it is logistically demanding, time inefficient, subject to low recapture rates, …

Uncertainty Aware Mapping Of Embedded Systems For Reliability, Performance, And Energy, Wenkai Guan, Milad Ghorbani Moghaddam, Cristinel Ababei

Electrical and Computer Engineering Faculty Research and Publications

Duo to technology downscaling, embedded systems have increased in complexity and heterogeneity. Increasingly large process, voltage, and temperature variations negatively affect the design and optimization process of these systems. These factors contribute to increased uncertainties that in turn undermine the accuracy and effectiveness of traditional design approaches. In this paper, we formulate the problem of uncertainty aware mapping for multicore embedded systems as a multi-objective optimization problem. We present a solution to this problem that integrates uncertainty models as a new design methodology constructed with Monto Carlo and evolutionary algorithms. The methodology is uncertainty aware because it is able to …

Experimental Validation Of External Load Effects For Micro-Contacts Under Low Frequency, Low Amplitude Alternating Current (Ac) Test Conditions, Protap Mahanta, Ronald A. Coutu Jr., Dushyant Tomer

Electrical and Computer Engineering Faculty Research and Publications

The use of micro-contacts has been demonstrated in various radio frequency (RF) applications. However, the premature failure of such devices under alternating current (AC) operations is still a hurdle to further development. In this work, modified gray scale lithography is performed to fabricate two types of gold–gold (Au–Au) micro-contacts: hemispherical-planar and hemispherical-2D pyramid. The performance of these devices was investigated under low frequency, low amplitude AC conditions with external circuit loads. A custom-made experimental setup which uses various load configurations, controls the frequency of the applied voltage and modifies the cycle rate of switch operation to obtain the contact resistance …

Remote Vibration Estimation Using Displaced-Phase-Center Antenna Sar For Strong Clutter Environments, Justin B. Campbell, Francisco Pérez, Qi Wang, Balasubramaniam Santhanam, Ralf Dunkel, Armin W. Doerry, Thomas Atwood, Majeed M. Hayat

Electrical and Computer Engineering Faculty Research and Publications

It has been previously demonstrated that it is possible to perform remote vibrometry using synthetic aperture radar (SAR) in conjunction with the discrete fractional Fourier transform (DFrFT). Specifically, the DFrFT estimates the chirp parameters (related to the instantaneous acceleration of a vibrating object) of a slow-time signal associated with the SAR image. However, ground clutter surrounding a vibrating object introduces uncertainties in the estimate of the chirp parameter retrieved via the DFrFT method. To overcome this shortcoming, various techniques based on subspace decomposition of the SAR slow-time signal have been developed. Nonetheless, the effectiveness of these techniques is limited to …

Investigation Of Lstm Based Prediction For Dynamic Energy Management In Chip Multiprocessors, Milad Ghorbani Moghaddam, Wenkai Guan, Cristinel Ababei

Electrical and Computer Engineering Faculty Research and Publications

In this paper, we investigate the effectiveness of using long short-term memory (LSTM) instead of Kalman filtering to do prediction for the purpose of constructing dynamic energy management (DEM) algorithms in chip multi-processors (CMPs). Either of the two prediction methods is employed to estimate the workload in the next control period for each of the processor cores. These estimates are then used to select voltage-frequency (VF) pairs for each core of the CMP during the next control period as part of a dynamic voltage and frequency scaling (DVFS) technique. The objective of the DVFS technique is to reduce energy consumption …

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 six 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, and then directs the solicitation and peer review of the papers. In cases where the GE/AE is also an author, …

H.264 Video Decoder Implemented On Fpgas Using 3×3 And 2×2 Networks-On-Chip, Ian Barge, Cristinel Ababei

Electrical and Computer Engineering Faculty Research and Publications

In this paper, we present the design and verification of the H.264 video decoder algorithm on FPGAs. The primary difference compared to previously reported designs is that the communication between the decoder modules is done via a network-on-chip in our case. The proposed design is a complete system level hardware design described in VHDL and Verilog. We report experimental results for two different implementations. The first implementation uses a 3×3 network-on-chip and is validated on the DE4 development board, which uses Altera's Stratix IV GX FPGA chip. The second implementation uses a 2×2 network-on-chip and is validated on the Cyclone …

Electronically Tuned Phase Transition In Germanium Telluride (Gete) Cells For Memory And Rf Switch Applications, Dushyant Tomer, Ronald A. Coutu Jr.

Electrical and Computer Engineering Faculty Research and Publications

Germanium telluride (GeTe) is a phase change material that undergoes an amorphous to crystalline transition upon heating to ~ 200oC. This transition is reversible in nature and results in ~ six orders of magnitude difference in GeTe resistivity which makes it a suitable candidate for data storage and other functional devices. In this work, micro-size phase change test cells were fabricated by RF sputtering GeTe thin films onto silicon (Si) wafers and Si wafers coated with silicon dioxide (SiO2), silicon nitride (Si3N4), and alumina (Al2O3) films. Two different heating methods, conductive and electrical (i.e. Joule heating), were applied to induce …

Analytical Formulas For Mean Gain And Excess Noise Factor In Inas Avalanche Photodiodes, Erum Jamil, Majeed M. Hayat, Gordon A. Keeler

Electrical and Computer Engineering Faculty Research and Publications

It has been known that McIntyre's local multiplication theory for avalanche photodiodes (APDs) does not fully explain the experimental results for single-carrier InAs APDs, which exhibit excess noise factor values below 2. While it has been established that the inclusion of the dead-space effect in the nonlocal multiplication theory resolves this discrepancy, no closed-form formulas for the mean gain and excess noise factor have been specialized to InAs APDs in a nonlocal setting. Upon utilizing prior analytical formulation of single-carrier avalanche multiplication based on age-dependent branching theory in conjunction with nonlocal ionization coefficients and thresholds for InAs, closed-form solutions of …

Deep Convolutional Particle Filter With Adaptive Correlation Maps For Visual Tracking, Reza Jilil Mozhdehi, Yevgeniy Vladimirovich Reznichenko, Abubakar Siddique, Henry P. Medeiros

Electrical and Computer Engineering Faculty Research and Publications

The robustness of the visual trackers based on the correlation maps generated from convolutional neural networks can be substantially improved if these maps are used to employed in conjunction with a particle filter. In this article, we present a particle filter that estimates the target size as well as the target position and that utilizes a new adaptive correlation filter to account for potential errors in the model generation. Thus, instead of generating one model which is highly dependent on the estimated target position and size, we generate a variable number of target models based on high likelihood particles, which …

Efficient Interconnectivity Among Networks Under Security Constraint, Pankaz Das, Rezoan A. Shuvro, Mahshid Rahnamay-Naeini, Nasir Ghani, Majeed M. Hayat

Electrical and Computer Engineering Faculty Research and Publications

Interconnectivity among networks is essential for enhancing communication capabilities of networks such as the expansion of geographical range, higher data rate, etc. However, interconnections may initiate vulnerability (e.g., cyber attacks) to a secure network due to introducing gateways and opportunities for security attacks such as malware, which may propagate from the less secure network. In this paper, the interconnectivity among subnetworks is maximized under the constraint of security risk. The dynamics of propagation of security risk is modeled by the evil-rain influence model and the SIR (Susceptible-Infected-Recovered) epidemic model. Through extensive numerical simulations using different network topologies and interconnection patterns, …

Efficiency Improvement Of Fault-Tolerant Three-Level Power Converters, Ramin Katebi, Jiangbiao He, Waqar A. Khan, Nathan Weise

Electrical and Computer Engineering Faculty Research and Publications

Fault-tolerant power converters play a critical role in the transportation electrification. However, fault-tolerant operation, high efficiency, and low cost usually result in design criteria that have conflicting constraints and goals. The majority of the fault-tolerant power converter topologies presented in the literature confirm these conflicts. In this paper, three types of fault-tolerant neutral-point clamped (NPC) converters are investigated. Various modulation strategies are explored to reduce the losses of the redundant phase leg. The simulation and experimental results show that the Switching Frequency Optimal Phase opposition Disposition modulation strategy is the most effective approach in minimizing the losses in the redundant …

Stochastic Search Methods For Mobile Manipulators, Amoako-Frimpong Samuel Yaw, Matthew Messina, Henry P. Medeiros, Jeremy Marvel, Roger Bostelman

Electrical and Computer Engineering Faculty Research and Publications

Mobile manipulators are a potential solution to the increasing need for additional flexibility and mobility in industrial applications. However, they tend to lack the accuracy and precision achieved by fixed manipulators, especially in scenarios where both the manipulator and the autonomous vehicle move simultaneously. This paper analyzes the problem of dynamically evaluating the positioning error of mobile manipulators. In particular, it investigates the use of Bayesian methods to predict the position of the end-effector in the presence of uncertainty propagated from the mobile platform. The precision of the mobile manipulator is evaluated through its ability to intercept retroreflective markers using …

Short-Term Load Forecasting Of Natural Gas With Deep Neural Network Regression, Gregory Merkel, Richard James Povinelli, Ronald H. Brown

Electrical and Computer Engineering Faculty Research and Publications

Deep neural networks are proposed for short-term natural gas load forecasting. Deep learning has proven to be a powerful tool for many classification problems seeing significant use in machine learning fields such as image recognition and speech processing. We provide an overview of natural gas forecasting. Next, the deep learning method, contrastive divergence is explained. We compare our proposed deep neural network method to a linear regression model and a traditional artificial neural network on 62 operating areas, each of which has at least 10 years of data. The proposed deep network outperforms traditional artificial neural networks by 9.83% weighted …

Detection And Quantification Of Multi-Analyte Mixtures Using A Single Sensor And Multi-Stage Data-Weighted Rlse, Karthick Sothivelr, Florian Bender, Fabien Josse, Edwin E. Yaz, Antonio J. Ricco

Electrical and Computer Engineering Faculty Research and Publications

This work reports the development and experimental verification of a sensor signal processing technique for online identification and quantification of aqueous mixtures of benzene, toluene, ethylbenzene, xylenes (BTEX) and 1, 2, 4-trimethylbenzene (TMB) at ppb concentrations using time-dependent frequency responses from a single polymer-coated shear-horizontal surface acoustic wave sensor. Signal processing based on multi-stage exponentially weighted recursive leastsquares estimation (EW-RLSE) is utilized for estimating the concentrations of the analytes in the mixture that are most likely to have produced a given sensor response. The initial stages of EW-RLSE are used to eliminate analyte(s) that are erroneously identified as present in …