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Electrical and Computer Engineering Faculty Research & Creative Works

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A Miniaturized Dual-Band Dual-Polarized Band-Notched Slot Antenna Array With High Isolation For Base Station Applications, Min Li, Rong Wang, Jamal Muhammad Yasir, Lijun Jiang Feb 2020

A Miniaturized Dual-Band Dual-Polarized Band-Notched Slot Antenna Array With High Isolation For Base Station Applications, Min Li, Rong Wang, Jamal Muhammad Yasir, Lijun Jiang

Electrical and Computer Engineering Faculty Research & Creative Works

In this article, a miniaturized dual-band dual-polarized slot antenna array is proposed for base station applications. It consists of two closely located $1\times 4$ subarrays for the digital cellular system (DCS) and wideband code division multiple access (WCDMA) operations. The band-notched slot antenna (BNSA) is designed and adopted as the subarray element with radiation-suppression characteristic at notch frequencies. The notch frequency for one subarray is designed at the center operating frequency of the other subarray. As a result, the radiation from DCS subarray could be effectively suppressed within the WCDMA band and vice versa, resulting in high isolation between two …

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Reduction In Absorption Edge Of The Digital-Alloyed Znmno Thin Films Grown Using Atomic Layer Deposition, Amirhossein Ghods, Chuanle Zhou, Ian T. Ferguson Jan 2020

Reduction In Absorption Edge Of The Digital-Alloyed Znmno Thin Films Grown Using Atomic Layer Deposition, Amirhossein Ghods, Chuanle Zhou, Ian T. Ferguson

Electrical and Computer Engineering Faculty Research & Creative Works

Transition metal doping has been used as a common approach for tuning the bandgap energy of zinc oxide (ZnO) based materials. In this work, manganese-doped ZnO (ZnMnO) thin films were grown using the atomic layer deposition (ALD) and used to study the effect of manganese incorporation in ZnO films. The effect of digital alloying on reducing the absorption edge of the ZnMnO thin films is studied by changing the ZnO to MnO cycle ratio during each ALD super-cycle. Room-temperature optical spectroscopic characterization showed a significant reduction in bandgap energy from 3.30 eV for pure ZnO to around 2.25 eV for …

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Autonomous Control Of A Line Follower Robot Using A Q-Learning Controller, Sepehr Saadatmand, Sima Azizi, Mohammadamir Kavousi, Donald C. Wunsch Jan 2020

Autonomous Control Of A Line Follower Robot Using A Q-Learning Controller, Sepehr Saadatmand, Sima Azizi, Mohammadamir Kavousi, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, a MIMO simulated annealing (SA)-based Q-learning method is proposed to control a line follower robot. The conventional controller for these types of robots is the proportional (P) controller. Considering the unknown mechanical characteristics of the robot and uncertainties such as friction and slippery surfaces, system modeling and controller designing can be extremely challenging. The mathematical modeling for the robot is presented in this paper, and a simulator is designed based on this model. The basic Q-learning methods are based pure exploitation and the ε -greedy methods, which help exploration, can harm the controller performance after learning completion …

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On The Effects Of High-K Dielectric Resurf In High-Voltage Bulk Finfets, Chia Hui Cheng, Jun Wei Lai, Kai Ting Hu, Chih Fang Huang, Feng Zhao Jan 2020

On The Effects Of High-K Dielectric Resurf In High-Voltage Bulk Finfets, Chia Hui Cheng, Jun Wei Lai, Kai Ting Hu, Chih Fang Huang, Feng Zhao

Electrical and Computer Engineering Faculty Research & Creative Works

High-K dielectric reduced surface field (RESURF) effects in high-voltage bulk FinFETs through three-dimensional simulation are discussed in this paper for the first time. Compared to a planar gate LDMOSFET where the length of the drift region is the same, dielectric RESURF significantly increases the optimal implant dose for the drift region to a higher value, although BV2/Ron,sp is similar. By using a high-K dielectric in the shallow trench isolation (STI) to further enhance the dielectric RESURF, the BV is increased and the Ron,sp is reduced, yielding a significantly improved BV2/Ron,sp, together with a better ON/OFF current ratio. However, with the …

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Artificial Synaptic Behavior Of Aloe Polysaccharides-Based Device With Au As Top Electrode, Z. X. Lim, I. A. Tayeb, Z. A.A. Hamid, M. F. Ain, A. M. Hashim, J. M. Abdullah, A. A. Sivkov, F. Zhao, K. Y. Cheong Jan 2020

Artificial Synaptic Behavior Of Aloe Polysaccharides-Based Device With Au As Top Electrode, Z. X. Lim, I. A. Tayeb, Z. A.A. Hamid, M. F. Ain, A. M. Hashim, J. M. Abdullah, A. A. Sivkov, F. Zhao, K. Y. Cheong

Electrical and Computer Engineering Faculty Research & Creative Works

Formulated, processed, and dried Aloe polysaccharides thin film sandwiched between ITO as bottom electrode and Au as top electrode has been adopted as an artificial synapse to emulate behavior of neuromorphic computing. The synaptic plasticity or weight has been modulated with this simple metal-insulator-metal structure by applying voltage sweep and voltage pulse, with excitatory postsynaptic current being monitored. Synaptic potentiation and depression have been demonstrated by applying 6 consecutive sweeps of voltage in positive and negative polarity, respectively. By varying number (10 - 50) of voltage pulses, variable synaptic weight has been measured with paired pulse facilitation and post-tetanic potentiation …

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A Novel Data-Driven Scheme For The Ship Wake Identification On The 2-D Dynamic Sea Surface, Yanming Zhang, Lijun Jiang Jan 2020

A Novel Data-Driven Scheme For The Ship Wake Identification On The 2-D Dynamic Sea Surface, Yanming Zhang, Lijun Jiang

Electrical and Computer Engineering Faculty Research & Creative Works

Because the ship wake spreads into an area much larger than that of the ship hull in the sea surface, it has been widely used in the ship detection. However, due to the complex sea wave motion and the high sea state, the ship wake detection is still a challenging task. In this paper, we propose a novel data-driven method based on dynamic mode decomposition (DMD) to detect, reconstruct, and locate the Kelvin wake on the two-dimensional dynamic sea surface. Through the proposed method, the sea's dynamic characteristics including the oscillation frequency and decay/growth rate of ship wakes and the …

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Incremental Cluster Validity Indices For Online Learning Of Hard Partitions: Extensions And Comparative Study, Leonardo Enzo Brito Da Silva, Niklas Max Melton, Donald C. Wunsch Jan 2020

Incremental Cluster Validity Indices For Online Learning Of Hard Partitions: Extensions And Comparative Study, Leonardo Enzo Brito Da Silva, Niklas Max Melton, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

Validation is one of the most important aspects of clustering, particularly when the user is designing a trustworthy or explainable system. However, most clustering validation approaches require batch calculation. This is an important gap because of the value of clustering in real-time data streaming and other online learning applications. Therefore, interest has grown in providing online alternatives for validation. This paper extends the incremental cluster validity index (iCVI) family by presenting incremental versions of Calinski-Harabasz (iCH), Pakhira-Bandyopadhyay-Maulik (iPBM), WB index (iWB), Silhouette (iSIL), Negentropy Increment (iNI), Representative Cross Information Potential (irCIP), Representative Cross Entropy (irH), and Conn_Index (iConn_Index). This paper …

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Off-Policy Q-Learning For Anti-Interference Control Of Multi-Player Systems, Jinna Li, Zhenfei Xiao, Tianyou Chai, Frank L. Lewis, Sarangapani Jagannathan Jan 2020

Off-Policy Q-Learning For Anti-Interference Control Of Multi-Player Systems, Jinna Li, Zhenfei Xiao, Tianyou Chai, Frank L. Lewis, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This paper develops a novel off-policy game Q-learning algorithm to solve the anti-interference control problem for discrete-time linear multi-player systems using only data without requiring system matrices to be known. The primary contribution of this paper lies in that the Q-learning strategy employed in the proposed algorithm is implemented in an off-policy policy iteration approach other than on-policy learning due to the well-known advantages of off-policy Q-learning over on-policy Q-learning. All of the players work hard together for the goal of minimizing their common performance index meanwhile defeating the disturbance that tries to maximize the specific performance index, and finally …

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Pseudospin-Polarized Topological Line Defects In Dielectric Photonic Crystals, Menglin L.N. Chen, Li (Lijun) Jun Jiang, Zhihao Lan, Wei E.I. Sha Jan 2020

Pseudospin-Polarized Topological Line Defects In Dielectric Photonic Crystals, Menglin L.N. Chen, Li (Lijun) Jun Jiang, Zhihao Lan, Wei E.I. Sha

Electrical and Computer Engineering Faculty Research & Creative Works

Electromagnetic (EM) topological insulators have been extensively explored due to the robust edge states they support. In this work, we propose a topological EM system based on a line defect in topologically nontrivial photonic crystals (PCs). With a finite-difference supercell approach, modal analysis of the PC structure is investigated in detail. The topological line-defect states are pseudospin polarized and their energy flow directions are determined by the corresponding pseudospin helicities. These states can be excited by using two spatially symmetric line-source arrays carrying orbital angular momenta. The feature of the unidirectional propagation is demonstrated, and it is stable when disorders …

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Enhanced Pml Based On The Long Short Term Memory Network For The Fdtd Method, He Ming Yao, Lijun Jiang Jan 2020

Enhanced Pml Based On The Long Short Term Memory Network For The Fdtd Method, He Ming Yao, Lijun Jiang

Electrical and Computer Engineering Faculty Research & Creative Works

This paper proposes a new absorbing boundary condition (ABC) computation approach based on the deep learning technique. Benefited from the sequence dependence feature, the Long Short-Term Memory (LSTM) network is employed to replace the conventional perfectly matched layer (PML) ABC for the Finite-Difference Time-Domain (FDTD) solving process. The newly proposed LSTM based PML model is trained by the electromagnetic field data on the interface of the conventional PML. Different from the conventional PML, the newly proposed model only needs one cell layer as the boundary. Hence, the newly proposed method conveniently reduces both the algorithm's complexity and the area of …

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Electromagnetic-Circuital-Thermal Multiphysics Simulation Method: A Review, Huan Huan Zhang, Pan Pan Wang, Shuai Zhang, Long Li, Ping Li, Wei E.I. Sha, Li (Lijun) Jun Jiang Jan 2020

Electromagnetic-Circuital-Thermal Multiphysics Simulation Method: A Review, Huan Huan Zhang, Pan Pan Wang, Shuai Zhang, Long Li, Ping Li, Wei E.I. Sha, Li (Lijun) Jun Jiang

Electrical and Computer Engineering Faculty Research & Creative Works

Electromagnetic-circuital-thermal multiphysics simulation is a very important topic in the field of integrated circuits (ICs), microwave circuits, antennas, etc. This paper presents a comprehensive review of the state of the art of electromagnetic-circuital-thermal multiphysics simulation method. Most efforts were focused on electromagnetic-circuital co-simulation and electromagnetic-thermal cosimulation. A brief introduction of related theories like governing equations, numerical methods, and coupling mechanisms is also included.

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Numerical Methods For Electromagnetic Modeling Of Graphene: A Review, Kaikun Niu, Ping Li, Zhixiang Huang, Li (Lijun) Jun Jiang, Hakan Bagci Jan 2020

Numerical Methods For Electromagnetic Modeling Of Graphene: A Review, Kaikun Niu, Ping Li, Zhixiang Huang, Li (Lijun) Jun Jiang, Hakan Bagci

Electrical and Computer Engineering Faculty Research & Creative Works

Graphene's remarkable electrical, mechanical, thermal, and chemical properties have made this the frontier of many other 2-D materials a focus of significant research interest in the last decade. Many theoretical studies of the physical mechanisms behind these properties have been followed by those investing the graphene's practical use in various fields of engineering. Electromagnetics, optics, and photonics are among these fields, where potential benefits of graphene in improving the device/system performance have been studied. These studies are often carried out using simulation tools. To this end, many numerical methods have been developed to characterize electromagnetic field/wave interactions on graphene sheets …

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Cagniard-Dehoop Technique-Based Computation Of Retarded Partial Coefficients: The Coplanar Case, Martin Stumpf, Giulio Antonini, Albert E. Ruehli Jan 2020

Cagniard-Dehoop Technique-Based Computation Of Retarded Partial Coefficients: The Coplanar Case, Martin Stumpf, Giulio Antonini, Albert E. Ruehli

Electrical and Computer Engineering Faculty Research & Creative Works

Efficient computation of partial elements plays a key role in the Partial Element Equivalent Circuit (PEEC) method. A novel analytical method for computing retarded partial coefficients based on the Cagniard-DeHoop (CdH) technique is proposed. The methodology is first theoretically developed and then illustrated on the computation of a surface retarded partial coefficient pertaining to two coplanar rectangular surface elements. An efficient way for incorporating loss mechanisms in the time domain (TD) via the Schouten-Van der Pol theorem is proposed. Illustrative numerical examples demonstrating the validity of the introduced solution are given.

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A Novel Calculation Method To Design Parasitic Decoupling Technique For Two Antennas, Min Li, Di Wu, Bing Xiao, Kwan Lawrence Yeung, Lijun Jiang Jan 2020

A Novel Calculation Method To Design Parasitic Decoupling Technique For Two Antennas, Min Li, Di Wu, Bing Xiao, Kwan Lawrence Yeung, Lijun Jiang

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, a systematic and calculation-based parasitic decoupling technique (PDT) is proposed to mitigate the mutual coupling between two closely coupled antennas. The adopted parasitic decoupling structure consists of two transmission lines connected to the feed lines of antennas and a parasitic element connected with a transmission line and terminated by a reactive load. Rigorous decoupling theory and systematic design procedures are presented. The lengths of transmission lines and value of reactive load can be precisely calculated to increase antenna isolation. The superiority of the proposed PDT is verified by four decoupling examples. The simulated and measured results show …

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Nonlinear Loss Model In Absorptive-Type Ferrite Frequency-Selective Limiters, Anatoliy O. Boryssenko, Scott M. Gillette, Marina Y. Koledintseva Dec 2019

Nonlinear Loss Model In Absorptive-Type Ferrite Frequency-Selective Limiters, Anatoliy O. Boryssenko, Scott M. Gillette, Marina Y. Koledintseva

Electrical and Computer Engineering Faculty Research & Creative Works

Absorptive-type ferrite-based frequency-selective limiters (FSLs) utilize nonlinear (NL) phenomena in magnetized ferrites to provide real-time analog signal processing of RF/microwave electromagnetic (EM) signals. There are no commercially available modeling tools that simulate these interactions, and the development and optimization of FSLs are largely done experimentally. FSL modeling and design is complicated by NL, multiscale, and Multiphysics nature of operation. In this article, an NL loss model in a ferrite is proposed and implemented in an efficient numerical algorithm. The equivalent linear magnetic loss tangent is represented in a closed form. A full-wave numerical EM model with high-fidelity meshing is set …

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Structured Iterative Hard Thresholding For Categorical And Mixed Data Types, Thy Nguyen, Tayo Obafemi-Ajayi Dec 2019

Structured Iterative Hard Thresholding For Categorical And Mixed Data Types, Thy Nguyen, Tayo Obafemi-Ajayi

Electrical and Computer Engineering Faculty Research & Creative Works

In many applications, data exists in a mixed data type format, i.e. a combination of nominal (categorical) and numerical features. A common practice for working with categorical features is to use an encoding method to transform the discrete values into numeric representation. However, numeric representation often neglects the innate structures in categorical features, potentially degrading the performance of learning algorithms. Utilizing the numeric representation could also limit interpretation of the learned model, such as finding the most discriminative categorical features or filtering irrelevant attributes. In this work, we extend the iterative hard thresholding (IHT) algorithm to quantify the structure of …

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Analysis And Introduction Of Effective Permeability With Additional Air-Gaps On Wireless Power Transfer Coils For Electric Vehicle Based On Sae J2954 Recommended Practice, Dongwook Kim, Hongseok Kim, Anfeng Huang, Qiusen He, Hanyu Zhang, Seungyoung Ahn, Yuyu Zhu, Jun Fan Dec 2019

Analysis And Introduction Of Effective Permeability With Additional Air-Gaps On Wireless Power Transfer Coils For Electric Vehicle Based On Sae J2954 Recommended Practice, Dongwook Kim, Hongseok Kim, Anfeng Huang, Qiusen He, Hanyu Zhang, Seungyoung Ahn, Yuyu Zhu, Jun Fan

Electrical and Computer Engineering Faculty Research & Creative Works

The wireless power transfer (WPT) method for electric vehicles (EVs) is becoming more popular, and to ensure the interoperability of WPT systems, the Society of Automotive Engineers (SAE) established the J2954 recommended practice (RP). It includes powering frequency, electrical parameters, specifications, testing procedures, and other contents for EV WPT. Specifically, it describes the ranges of self-inductances of the transmitting coil, the receiving coil, and coupling coefficient (k), as well as the impedance matching values of the WPT system. Following the electrical parameters listed in SAE J2954 RP is crucial to ensure the EV wireless charging system is interoperable. This paper …

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Energy-Performance Scalability Analysis Of A Novel Quasi-Stochastic Computing Approach, Prashanthi Metku, Ramu Seva, Minsu Choi Dec 2019

Energy-Performance Scalability Analysis Of A Novel Quasi-Stochastic Computing Approach, Prashanthi Metku, Ramu Seva, Minsu Choi

Electrical and Computer Engineering Faculty Research & Creative Works

Stochastic computing (SC) is an emerging low-cost computation paradigm for efficient approximation. It processes data in forms of probabilities and offers excellent progressive accuracy. Since SC's accuracy heavily depends on the stochastic bitstream length, generating acceptable approximate results while minimizing the bitstream length is one of the major challenges in SC, as energy consumption tends to linearly increase with bitstream length. To address this issue, a novel energy-performance scalable approach based on quasi-stochastic number generators is proposed and validated in this work. Compared to conventional approaches, the proposed methodology utilizes a novel algorithm to estimate the computation time based on …

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Novel Cyber Fault Prognosis And Resilience Control For Cyber-Physical Systems, Shanshan Bi, Tianchen Wang, Lei Wang, Maciej Zawodniok Dec 2019

Novel Cyber Fault Prognosis And Resilience Control For Cyber-Physical Systems, Shanshan Bi, Tianchen Wang, Lei Wang, Maciej Zawodniok

Electrical and Computer Engineering Faculty Research & Creative Works

Cyber-physical systems (CPSs) consist of a network, computation, and physical process. Embedded networks, which deliver control and sensing signal, can potentially affect CPSs performance. However, the degradation of physical system performance caused by the embedded networks is frequently oversimplified with strong assumptions. The proposed scheme effectively relaxes those assumptions in the existing works that network delays are bounded in a specific range, or its distribution is time invariant. Most of the existing works on fault diagnosis and prognosis addressed the physical system fault detection and isolation and ignore cyber network faults. A novel cyber network fault prognosis scheme is proposed …

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Sparsity Constrained Regression For High-Speed Signal Integrity Modeling, Jiacheng Zhuo, Jiayi He, Zurab Kiguradze, Bhyrav Mutnury, James Drewniak Dec 2019

Sparsity Constrained Regression For High-Speed Signal Integrity Modeling, Jiacheng Zhuo, Jiayi He, Zurab Kiguradze, Bhyrav Mutnury, James Drewniak

Electrical and Computer Engineering Faculty Research & Creative Works

High-speed signal integrity (SI) modeling usually involves modeling non-linear subsystems. Traditional approaches like response surface modeling (RSM), artificial neural networks (ANN) and support vector machine (SVM) suffer from two major issues. Either they don't scale well when the number of dimensions or variables increase in the non-linear model, or they are sensitive to the initial training data used to create the models. For example: RSM approach requires large design of experiments (DoE) when the number of variables increase. With ANN, the designer has to spend a lot of time tuning or optimizing the hyperparameters. In this paper, a new approach …

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Bayesian Optimization For High-Speed Channel Equalization, Zurab Kiguradze, Nana Dikhaminjia, Mikheil Tsiklauri, Jiayi He, Bhyrav Mutnury, Arun Chada, James Drewniak Dec 2019

Bayesian Optimization For High-Speed Channel Equalization, Zurab Kiguradze, Nana Dikhaminjia, Mikheil Tsiklauri, Jiayi He, Bhyrav Mutnury, Arun Chada, James Drewniak

Electrical and Computer Engineering Faculty Research & Creative Works

Equalization methods are used to recover the signal attenuated by channel loss. Different optimization algorithms are applied to find the best tap coefficients for each equalization that will improve eye opening and reduce bit error rate. The goal function for most equalization optimization algorithms is to reduce the difference between input and output signals, which is a linear optimization problem and can be solved relatively easily. This indirectly will increase eye height and improve eye diagram. Directly optimizing eye height is a non-linear problem and cannot be solved with analytical method. We are proposing FFE and DFE combined equalization optimization …

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Design And Sensitivity Analysis Of Ebg Stripline Common-Mode Filters, Marina Y. Koledintseva, Sergiu Radu, Joseph Nuebel Dec 2019

Design And Sensitivity Analysis Of Ebg Stripline Common-Mode Filters, Marina Y. Koledintseva, Sergiu Radu, Joseph Nuebel

Electrical and Computer Engineering Faculty Research & Creative Works

Workflow of electromagnetic bandgap (EBG) common-mode (CM) filter design of edge-coupled differential pairs on a printed circuit board (PCB) and sensitivity of its characteristics to variations of geometrical and material parameters are discussed. A number of simple 20-GHz EBG CM notch filters for differential strip line pairs are designed using full-wave numerical electromagnetic modeling, fabricating, and testing. The cases of one and two strip line differential pairs crossing the EBG patches are considered. The modeled and measured mixed-mode S-parameters are analyzed as functions of geometrical parameters, including size and number of EBG patches, gaps between them, geometry and position of …

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Detection And Mitigation Of Attacks In Nonlinear Stochastic System Using Modified Detector, Chandreyee Bhowmick, S. Jagannathan Dec 2019

Detection And Mitigation Of Attacks In Nonlinear Stochastic System Using Modified Detector, Chandreyee Bhowmick, S. Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

A novel attack detection method is presented for a nonlinear system with known dynamics using the measured output in the presence of additive process and measurement noise. False data injection (FDI) and replay attacks are considered using a modified fault detector. The difference between the measured and the estimated output from an adaptive observer, often known as the innovation signal, is generated and shown to have a Gaussian distribution with non-zero mean. This innovation signal in conjunction with the modified detector is utilized to detect attacks under a stable controller using the estimated state vector. Unlike FDI attack, where the …

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Neutron Detection Performance Of Gallium Nitride Based Semiconductors, Chuanle Zhou, Andrew G. Melton, Eric Burgett, Nolan Hertel, Ian T. Ferguson Dec 2019

Neutron Detection Performance Of Gallium Nitride Based Semiconductors, Chuanle Zhou, Andrew G. Melton, Eric Burgett, Nolan Hertel, Ian T. Ferguson

Electrical and Computer Engineering Faculty Research & Creative Works

Neutron detection is crucial for particle physics experiments, nuclear power, space and international security. Solid state neutron detectors are of great interest due to their superior mechanical robustness, smaller size and lower voltage operation compared to gas detectors. Gallium nitride (GaN), a mature wide bandgap optoelectronic and electronic semiconductor, is attracting research interest for neutron detection due to its radiation hardness and thermal stability. This work investigated thermal neutron scintillation detectors composed of GaN thin films with and without conversion layers or rare-earth doping. Intrinsic GaN-based neutron scintillators are demonstrated via the intrinsic 14N(n, p) reaction, which has a small …

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Strain-Stress Study Of Alxga1−Xn/Ain Heterostructures On C-Plane Sapphire And Related Optical Properties, Yining Feng, Vishal Saravade, Ting Fung Chung, Yongqi Dong, Hua Zhou, Bahadir Kucukgok, Ian T. Ferguson, Na Lu Dec 2019

Strain-Stress Study Of Alxga1−Xn/Ain Heterostructures On C-Plane Sapphire And Related Optical Properties, Yining Feng, Vishal Saravade, Ting Fung Chung, Yongqi Dong, Hua Zhou, Bahadir Kucukgok, Ian T. Ferguson, Na Lu

Electrical and Computer Engineering Faculty Research & Creative Works

This work presents a systematic study of stress and strain of AlxGa1−xN/AlN with composition ranging from GaN to AlN, grown on a c-plane sapphire by metal-organic chemical vapor deposition, using synchrotron radiation high-resolution X-ray diffraction and reciprocal space mapping. The c-plane of the AlxGa1−xN epitaxial layers exhibits compressive strain, while the a-plane exhibits tensile strain. The biaxial stress and strain are found to increase with increasing Al composition, although the lattice mismatch between the AlxGa1−xN and the buffer layer AlN gets smaller. A reduction in the lateral coherence lengths and an increase in the edge and …

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E-Mobility -- Advancements And Challenges, Aswad Adib, Khurram K. Afridi, Mahshid Amirabadi, Fariba Fateh, Mehdi Ferdowsi, Brad Lehman, Laura H. Lewis, Behrooz Mirafzal, Maryam Saeedifard, Mohammad B. Shadmand, Pourya Shamsi Nov 2019

E-Mobility -- Advancements And Challenges, Aswad Adib, Khurram K. Afridi, Mahshid Amirabadi, Fariba Fateh, Mehdi Ferdowsi, Brad Lehman, Laura H. Lewis, Behrooz Mirafzal, Maryam Saeedifard, Mohammad B. Shadmand, Pourya Shamsi

Electrical and Computer Engineering Faculty Research & Creative Works

Mobile platforms cover a broad range of applications from small portable electric devices, drones, and robots to electric transportation, which influence the quality of modern life. The end-to-end energy systems of these platforms are moving toward more electrification. Despite their wide range of power ratings and diverse applications, the electrification of these systems shares several technical requirements. Electrified mobile energy systems have minimal or no access to the power grid, and thus, to achieve long operating time, ultrafast charging or charging during motion as well as advanced battery technologies are needed. Mobile platforms are space-, shape-, and weight-constrained, and therefore, …

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An Optimal Hybrid Learning Approach For Attack Detection In Linear Networked Control Systems, Haifeng Niu, Avimanyu Sahoo, Chandreyee Bhowmick, S. Jagannathan Nov 2019

An Optimal Hybrid Learning Approach For Attack Detection In Linear Networked Control Systems, Haifeng Niu, Avimanyu Sahoo, Chandreyee Bhowmick, S. Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

A novel learning-based attack detection and estimation scheme is proposed for linear networked control systems NCS, wherein the attacks on the communication network in the feedback loop are expected to increase network induced delays and packet losses, thus changing the physical system dynamics. First, the network traffic flow is modeled as a linear system with uncertain state matrix and an optimal Q-learning based control scheme over finite-horizon is utilized to stabilize the flow. Next, an adaptive observer is proposed to generate the detection residual, which is subsequently used to determine the onset of an attack when it exceeds a predefined …

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Two-Step Enhanced Deep Learning Approach For Electromagnetic Inverse Scattering Problems, He Ming Yao, Wei E.I. Sha, Lijun Jiang Nov 2019

Two-Step Enhanced Deep Learning Approach For Electromagnetic Inverse Scattering Problems, He Ming Yao, Wei E.I. Sha, Lijun Jiang

Electrical and Computer Engineering Faculty Research & Creative Works

In this letter, a new deep learning (DL) approach is proposed to solve the electromagnetic inverse scattering (EMIS) problems. The conventional methods for solving inverse problems face various challenges including strong ill-conditions, high contrast, expensive computation cost, and unavoidable intrinsic nonlinearity. To overcome these issues, we propose a new two-step machine learning based approach. In the first step, a complex-valued deep convolutional neural network is employed to retrieve initial contrasts (permittivity's) of dielectric scatterers from measured scattering data. In the second step, the previously obtained contrasts are input into a complex-valued deep residual convolutional neural network to refine the reconstruction …

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Biomarker Discovery In Inflammatory Bowel Diseases Using Network-Based Feature Selection, Mostafa Abbas, John Matta, Thanh Le, Halima Bensmail, Tayo Obafemi-Ajayi, Vasant Honavar, Yasser El-Manzalawy Nov 2019

Biomarker Discovery In Inflammatory Bowel Diseases Using Network-Based Feature Selection, Mostafa Abbas, John Matta, Thanh Le, Halima Bensmail, Tayo Obafemi-Ajayi, Vasant Honavar, Yasser El-Manzalawy

Electrical and Computer Engineering Faculty Research & Creative Works

Reliable identification of Inflammatory biomarkers from metagenomics data is a promising direction for developing non-invasive, cost-effective, and rapid clinical tests for early diagnosis of IBD. We present an integrative approach to Network-Based Biomarker Discovery (NBBD) which integrates network analyses methods for prioritizing potential biomarkers and machine learning techniques for assessing the discriminative power of the prioritized biomarkers. Using a large dataset of new-onset pediatric IBD metagenomics biopsy samples, we compare the performance of Random Forest (RF) classifiers trained on features selected using a representative set of traditional feature selection methods against NBBD framework, configured using five different tools for inferring …

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Data Collection And Analysis Techniques For Solar Car Telemetry Data, Michael Rouse, Miranda Sauer, Kurt Louis Kosbar Oct 2019

Data Collection And Analysis Techniques For Solar Car Telemetry Data, Michael Rouse, Miranda Sauer, Kurt Louis Kosbar

Electrical and Computer Engineering Faculty Research & Creative Works

Data collected from a solar car is monitored in real-time, which allows for intelligent decision making, efficient debugging, and high-quality testing for solar car teams. This paper compares three databases (MySQL, PostgreSQL, and MongoDB) to determine the optimal database system that should be used at solar car competitions. Each database system was tested using simulated solar car data to measure read and write speeds, and quality of performance on a low-power computer. Data were analyzed and displayed with custom interfaces to improve the user experience at solar car competitions.

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