Department of Electrical and Computer Engineering
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Item 3-D-Printed CRLH Metamaterial-Enabled Electrically Small Antenna(IEEE Antennas and Wireless Propagation Letters, 2023-11-29) Li, Shuping; Lazarus, Nathan; Klemash, Mary E. Galanko; Bedair, Sarah S.; Wu, Chung-Tse MichaelThis letter presents a 3-D-printed composite right/left-handed (CRLH) metamaterial-enabled electrically small antenna (ESA) in the 300 MHz band. A 3-D conical helix strip is loaded by surrounding an electrical small monopole antenna, with a length of 0.02 λ0 (free space wavelength), which is vertically placed over a finite ground plane. The proposed ESA is based on the 3-D realization of an open-ended CRLH resonator, of which the electrical size is ka = 0.11. An equivalent circuit model is provided with corresponding circuit parameters to derive the frequency response of the proposed 3-D-CRLH ESA. A prototype is fabricated using a widely available 3-D print technology, fused filament fabrication, combined with copper electro- and electroless plating. Experimental verification of the antenna demonstrates a monopole-like radiation pattern with a peak measured gain of −5 dBi, which is suitable to be integrated into compact wireless systems.Item A Coherent Integration Method for Moving Target Detection in a Parameter Jittering Radar System Based on Signum Coding(IEEE Signal Processing Letters, 2022-11-04) Huang, Penghui; Xia, Xiang-Gen; Wang, Lingyu; Liu, Xingzhao; Liao, GuishengIn this letter, we propose a novel long-time coherent integration detection method to detect an uncooperative moving target in a frequency and pulse repetition interval randomly jittering radar system based on signum coding (SC). In the proposed algorithm, an additional reference waveform is applied to eliminate the third-order harmonic influence induced by SC. Then, a generalized Keystone transform (GKT) is proposed to resolve the complex coupling among the range frequency, jittered carrier frequency, and nonuniformly sampled time. Simulation results are presented to validate the effectiveness and feasibility of the proposed method.Item A mechanistic stochastic framework for regulating bacterial cell division(Nature Publishing Group, 2016-07-26) Ghusinga,Khem Raj; Vargas-Garcia,Cesar A.; Singh,Abhyudai; Khem Raj Ghusinga, Cesar A. Vargas-Garcia,Abhyudai Singh; Singh, AbhyudaiHow exponentially growing cells maintain size homeostasis is an important fundamental problem. Recent single-cell studies in prokaryotes have uncovered the adder principle, where cells add a fixed size (volume) from birth to division, irrespective of their size at birth. To mechanistically explain the adder principle, we consider a timekeeper protein that begins to get stochastically expressed after cell birth at a rate proportional to the volume. Cell-division time is formulated as the first-passage time for protein copy numbers to hit a fixed threshold. Consistent with data, the model predicts that the noise in division timing increases with size at birth. Intriguingly, our results show that the distribution of the volume added between successive cell-division events is independent of the newborn cell size. This was dramatically seen in experimental studies, where histograms of the added volume corresponding to different newborn sizes collapsed on top of each other. The model provides further insights consistent with experimental observations: the distribution of the added volume when scaled by its mean becomes invariant of the growth rate. In summary, our simple yet elegant model explains key experimental findings and suggests a mechanism for regulating both the mean and fluctuations in cell-division timing for controlling size.Item A Simple Family of Non-Linear Analog Codes(IEEE Communications Letters, 2023-09-18) Burich, Mariano Eduardo; Garcia-Frias, JavierWe propose novel non-linear graph-based analog codes that directly encode k real-valued source samples into n real-valued samples by using (non-linear) sample-by-sample soft quantization of the input samples followed by a linear transformation on the soft-quantized values. Different from existing analog coding schemes, the proposed analog codes are able to produce additional output symbols in a rateless manner and can be decoded utilizing message passing algorithms dealing with real-valued nodes, achieving a performance close to the theoretical limits.Item A unified understanding of magnetorheological elastomers for rapid and extreme stiffness tuning(RSC Applied Polymers, 2023-10-02) Barron, Edward J.; Williams, Ella T.; Tutika, Ravi; Lazarus, Nathan; Bartlett, Michael D.Magnetorheological elastomers (MREs), which adapt their mechanical properties in response to a magnetic field, can enable changes in stiffness and shape for applications ranging from vibration isolators to shape morphing robots and soft adaptive grippers. Here, a unified design approach is introduced to create MRE materials for extreme stiffness tuning, up to 70×, with rapid (∼20 ms) and reversible shape change. This guides the creation of a hybrid MRE composite architecture that incorporates a combination of magnetic particles and magnetic fluids into elastomers. The role of both solid and fluid inclusions on magnetorheological response is systematically investigated and a predictive model is developed that captures the stiffness tuning response of MREs across diverse material microstructures and compositions. This general understanding enables MRE materials with programmable response and greatly enhanced stiffness tuning and rapid response times compared to many MRE, granular jamming, and phase change approaches. This insight is utilized to optimize composites for a soft adaptive gripper which grasps and releases objects of diverse geometries.Item A Universal Electric Vehicle Outlet and Portable Cable for North America(World Electric Vehicle Journal, 2024-08-06) Kempton, Willett; McGee, Rodney T.; Ejzak, Garrett A.For electric vehicle (EV) charging in North America, three AC connectors are standardized, resulting in a proliferation of charging stations which can only charge one of the three types of EV. We propose a “Universal EV Outlet” that works with an EV “carry along” charging cable—one end of the cable has a connector specific to that user’s EV, the other a plug for the Universal EV Outlet. This proposal does not interfere with, nor require change to, any existing charging stations. It does not require any new types of inlets on EVs. The components are already standardized. Eight use cases are examined to illustrate the advantages, and some limitations, of the Universal EV Outlet. The use cases illustrate how this solution: resolves the problem of multiple AC charging connectors, makes today’s “EV Ready” building codes more adaptable, lowers capital and maintenance costs, creates a solution to curbside and urban charging, increases energy efficiency, enables higher power three-phase AC charging for heavy vehicles, and facilitates use of EVs for building backup power and for vehicle-to-grid. Finally, we propose a standards-based active cable used with the Universal EV Outlet, which would allow fast and secure EV identification for curbside or other shared charging locations, usable today without modifications to current EVs.Item Accelerating manufacturing for biomass conversion via integrated process and bench digitalization: a perspective(Reaction Chemistry and Engineering, 2022-01-25) Batchu, Sai Praneet; Hernandez, Borja; Malhotra, Abhinav; Fang, Hui; Ierapetritou, Marianthi; Vlachos, Dionisios G.We present a perspective for accelerating biomass manufacturing via digitalization. We summarize the challenges for manufacturing and identify areas where digitalization can help. A profound potential in using lignocellulosic biomass and renewable feedstocks, in general, is to produce new molecules and products with unmatched properties that have no analog in traditional refineries. Discovering such performance-advantaged molecules and the paths and processes to make them rapidly and systematically can transform manufacturing practices. We discuss retrosynthetic approaches, text mining, natural language processing, and modern machine learning methods to enable digitalization. Laboratory and multiscale computation automation via active learning are crucial to complement existing literature and expedite discovery and valuable data collection without a human in the loop. Such data can help process simulation and optimization select the most promising processes and molecules according to economic, environmental, and societal metrics. We propose the close integration between bench and process scale models and data to exploit the low dimensionality of the data and transform the manufacturing for renewable feedstocks.Item AI Cannot Understand Memes: Experiments with OCR and Facial Emotions(Computers, Materials & Continua, 2021-05-11) Priyadarshini, Ishaani; Cotton, ChaseThe increasing capabilities of Artificial Intelligence (AI), has led researchers and visionaries to think in the direction of machines outperforming humans by gaining intelligence equal to or greater than humans, which may not always have a positive impact on the society. AI gone rogue, and Technological Singularity are major concerns in academia as well as the industry. It is necessary to identify the limitations of machines and analyze their incompetence, which could draw a line between human and machine intelligence. Internet memes are an amalgam of pictures, videos, underlying messages, ideas, sentiments, humor, and experiences, hence the way an internet meme is perceived by a human may not be entirely how a machine comprehends it. In this paper, we present experimental evidence on how comprehending Internet Memes is a challenge for AI. We use a combination of Optical Character Recognition techniques like Tesseract, Pixel Link, and East Detector to extract text from the memes, and machine learning algorithms like Convolutional Neural Networks (CNN), Region-based Convolutional Neural Networks (RCNN), and Transfer Learning with pre-trained denseNet for assessing the textual and facial emotions combined. We evaluate the performance using Sensitivity and Specificity. Our results show that comprehending memes is indeed a challenging task, and hence a major limitation of AI. This research would be of utmost interest to researchers working in the areas of Artificial General Intelligence and Technological Singularity.Item Air Moving Target Indication in Nadir Region for Spaceborne Surveillance Radar Systems(IEEE Geoscience and Remote Sensing Letters, 2023-06-02) Zou, Zihao; Huang, Penghui; Lin, Xin; Xia, Xiang-Gen; Xi, Peili; Sun, Yongyan; Liu, XingzhaoFor air moving target indication (AMTI) in nadir region, due to the fact that a spaceborne radar beam can illuminate the top of fuselage, the target radar cross Section is usually high, which is beneficial for the detection of a low-observable target. However, due to the short slant range, specular reflection effect, and relatively low radar ground resolution, the power of clutter component from nadir region is comparatively high, leading to the insufficient clutter suppression and the degradation of target detection performance. Fortunately, when an air moving target is adequately high, the target echo can be separated from the main clutter echoes due to a shorter time delay, making it possible to be only mixed with low-power ambiguous clutter echoes. Based on these considerations, this letter analyzes the performance of AMTI in nadir region for a spaceborne surveillance radar system. It analyzes the target minimum detectable velocities with different target heights and beam center elevation angles. Also, an effective sample selection method based on adaptive range segmentation is proposed to solve the power heterogeneity issue between the main clutter area and the range ambiguous clutter area. As a conclusion, the larger the elevation angle of an air moving target is, the higher the minimum target detectable height is.Item An Efficient Refocusing Method for Ground Moving Targets in Multichannel SAR Imagery(IEEE Geoscience and Remote Sensing Letters, 2024-08-02) Ma, Jingtao; Xia, Xiang-Gen; Wang, Jiannan; Tao, Haihong; Liao, Guisheng; Huang, PenghuiThis letter proposes a fast Doppler parameter estimation and refocusing method for ground moving targets in a synthetic aperture radar (SAR) system. In the proposed method, after implementing the main-lobe clutter rejection by using the azimuth adaptive processing technique, the range-azimuth positions of smeared target scatterers can be obtained via the constant false alarm rate (CFAR) detection. Then, an autocorrelation function is constructed to transform a moving target signal into the time-frequency plane, where the target parameters can be precisely and efficiently estimated by applying the scaled fast Fourier transform (FFT). Finally, ground moving targets can be well refocused and relocated in a SAR imagery. Compared with the conventional methods, the target output SNR can be enlarged about 3 dB under the low SNR by using the proposed parameter estimation method.Item An Empirical Loss Model for an Additively Manufactured Luneburg Lens Antenna(The Applied Computational Electromagnetics Society Journal, 2022-11-14) LaRocca, Brian F.; Mirotznik, Mark S.This research applies Effective Medium Theory and 3D Finite Element Analysis to model the transmissive loss through a waveguide fed additively manufactured Luneburg lens. New results are presented that provide rational function approximations for accurately modeling the aperture, beam, and radiation loss factors of the antenna. It introduces a normalized loss tangent and shows that the loss factors are dependent on the product of this parameter and the lens radius. Applying the constraint that the main beam of the radiation pattern contains 50% of accepted power, a maximum useful radius is tabulated for common polymers used in additive manufacturing.Item Array-Beamspace Mapping for Planar Two-Dimensional Beam-Forming(IEEE Access, 2023-07-21) Beardell, William L.; Murakowski, Janusz; Schneider, Garrett J.; Prather, Dennis W.As sixth-generation (6G) communication systems manifest at carrier frequencies well into the millimeter-wave (mmW) spectrum, the ability of conventional digital beamforming techniques to handle the beam-bandwidth product is increasingly stressed. Microwave photonic beamforming has been presented as a solution to this problem by up-converting a sampled RF field distribution to an optical carrier for analog beam-space processing, but to date has relied upon fiber arrays with the same dimensionality as the RF array, i.e., a two-dimensional RF array requires a two-dimensional fiber array and a three-dimensional optical processor to perform the Fourier transform required for two-dimensional beamforming. To address this problem, we present an approach to photonic mmW beamforming wherein two-dimensional phase information is preserved through a one-dimensional Fourier transform leveraging grating lobes in the array response. This approach carries several benefits, primarily as an enabler for leveraging photonic integrated circuits for RF-photonic beamforming, carrying with it a footprint reduction of more than ten thousand times. Furthermore, beamforming efficiency is increased for sources near the limits of the RF field-of-view; improvements to throughput power in such cases are as much as double. Theory, simulations, and experimental results in the form of images and videos are presented to validate the approach for a nineteen-element hexagonally-distributed phased array.Item Automatic detection and classification of bearded seal vocalizations in the northeastern Chukchi Sea using convolutional neural networks(The Journal of the Acoustical Society of America, 2022-01-19) Escobar-Amado, Christian D.; Badiey, Mohsen; Pecknold, SeanBearded seals vocalizations are often analyzed manually or by using automatic detections that are manually validated. In this work, an automatic detection and classification system (DCS) based on convolutional neural networks (CNNs) is proposed. Bearded seal sounds were year-round recorded by four spatially separated receivers on the Chukchi Continental Slope in Alaska in 2016–2017. The DCS is divided in two sections. First, regions of interest (ROI) containing possible bearded seal vocalizations are found by using the two-dimensional normalized cross correlation of the measured spectrogram and a representative template of two main calls of interest. Second, CNNs are used to validate and classify the ROIs among several possible classes. The CNNs are trained on 80% of the ROIs manually labeled from one of the four spatially separated recorders. When validating on the remaining 20%, the CNNs show an accuracy above 95.5%. To assess the generalization performance of the networks, the CNNs are tested on the remaining recorders, located at different positions, with a precision above 89.2% for the main class of the two types of calls. The proposed technique reduces the laborious task of manual inspection prone to inconstant bias and possible errors in detections.Item Beam Structured Channel Estimation for HF Skywave Massive MIMO-OFDM Communications(IEEE Transactions on Wireless Communications, 2024-08-14) Shi, Ding; Song, Linfeng; Gao, Xiqi; Wang, Jiaheng; Bengtsson, Mats; Li, Geoffrey Ye; Xia, Xiang-GenIn this paper, we investigate high frequency (HF) skywave massive multiple-input multiple-output (MIMO) communications with orthogonal frequency division multiplexing (OFDM) modulation. Based on the triple-beam (TB) based channel model and the channel sparsity in the TB domain, we propose a beam structured channel estimation (BSCE) approach. Specifically, we show that the space-frequency-time (SFT) domain estimator design for each TB domain channel element can be transformed into that of a low-dimensional TB domain estimator and the resulting SFT domain estimator is beam structured. We also present a method to select the TBs used for BSCE. Then we generalize the proposed BSCE by introducing window functions and a turbo principle to achieve a superior trade-off between complexity and performance. Furthermore, we present a low-complexity design and implementation of BSCE by exploiting the characteristics of the TB matrix. Simulation results validate the proposed theory and methods.Item Beamforming Based Full-Duplex for Millimeter-Wave Communication(MDPI AG, 2016-07-21) Liu,Xiao; Xiao,Zhenyu; Bai,Lin; Choi,Jinho; Xia,Pengfei; Xia,Xiang-Gen; Xiao Liu, Zhenyu Xiao, Lin Bai, Jinho Choi, Pengfei Xia, Xiang-Gen Xia; Xia, Xiang-GenIn this paper, we study beamforming based full-duplex (FD) systems in millimeter-wave (mmWave) communications. A joint transmission and reception (Tx/Rx) beamforming problem is formulated to maximize the achievable rate by mitigating self-interference (SI). Since the optimal solution is difficult to find due to the non-convexity of the objective function, suboptimal schemes are proposed in this paper. A low-complexity algorithm, which iteratively maximizes signal power while suppressing SI, is proposed and its convergence is proven. Moreover, two closed-form solutions, which do not require iterations, are also derived under minimum-mean-square-error (MMSE), zero-forcing (ZF), and maximum-ratio transmission (MRT) criteria. Performance evaluations show that the proposed iterative scheme converges fast (within only two iterations on average) and approaches an upper-bound performance, while the two closed-form solutions also achieve appealing performances, although there are noticeable differences from the upper bound depending on channel conditions. Interestingly, these three schemes show different robustness against the geometry of Tx/Rx antenna arrays and channel estimation errors.Item Block-based spectral image reconstruction for compressive spectral imaging using smoothness on graphs(Optics Express, 2022-02-17) Florez-Ospina, Juan F.; Alrushud, Abdullah K. M.; Lau, Daniel L.; Arce, Gonzalo R.A novel reconstruction method for compressive spectral imaging is designed by assuming that the spectral image of interest is sufficiently smooth on a collection of graphs. Since the graphs are not known in advance, we propose to infer them from a panchromatic image using a state-of-the-art graph learning method. Our approach leads to solutions with closed-form that can be found efficiently by solving multiple sparse systems of linear equations in parallel. Extensive simulations and an experimental demonstration show the merits of our method in comparison with traditional methods based on sparsity and total variation and more recent methods based on low-rank minimization and deep-based plug-and-play priors. Our approach may be instrumental in designing efficient methods based on deep neural networks and covariance estimation.Item Central Attention Network for Hyperspectral Imagery Classification(IEEE Transactions on Neural Networks and Learning Systems, 2022-03-10) Liu, Huan; Li, Wei; Xia, Xiang-Gen; Zhang, Mengmeng; Gao, Chen-Zhong; Tao, RanIn this article, the intrinsic properties of hyperspectral imagery (HSI) are analyzed, and two principles for spectral-spatial feature extraction of HSI are built, including the foundation of pixel-level HSI classification and the definition of spatial information. Based on the two principles, scaled dot-product central attention (SDPCA) tailored for HSI is designed to extract spectral-spatial information from a central pixel (i.e., a query pixel to be classified) and pixels that are similar to the central pixel on an HSI patch. Then, employed with the HSI-tailored SDPCA module, a central attention network (CAN) is proposed by combining HSI-tailored dense connections of the features of the hidden layers and the spectral information of the query pixel. MiniCAN as a simplified version of CAN is also investigated. Superior classification performance of CAN and miniCAN on three datasets of different scenarios demonstrates their effectiveness and benefits compared with state-of-the-art methods.Item Channel Estimation for Massive MIMO: An Information Geometry Approach(IEEE Transactions on Signal Processing, 2022-10-04) Yang, Jiyuan; Lu, An-An; Chen, Yan; Gao, Xiqi; Xia, Xiang-Gen; Slock, Dirk T. M.In this paper, we investigate the channel estimation for massive multi-input multi-output orthogonal frequency division multiplexing (MIMO-OFDM) systems. Using the sampled steering vectors in the space and frequency domain, we first establish a space-frequency (SF) beam based statistical channel model. The accuracy of the channel model can be guaranteed with sufficient sampling steering vectors. With the channel model, the channel estimation is formulated as obtaining the a posteriori information of the beam domain channel. We solve this problem by calculating an approximation of the a posteriori distribution's marginals within the information geometry framework. Specifically, by viewing the set of Gaussian distributions and the set of the marginals as a manifold and its e -flat submanifold, we turn the calculation of the marginals into an iterative projection process between submanifolds with different constraints. We derive the information geometry approach (IGA) for channel estimation by calculating the solutions of projections. We prove that the mean of the approximate marginals at the equilibrium of IGA is equal to that of the a posteriori distribution. Simulations demonstrate that the proposed IGA can accurately estimate the beam domain channel within limited iterations.Item Characterization of Voltage Stabilization Functions of Residential PV Inverters in a Power Hardware-in-the-Loop Environment(IEEE Access, 2022-10-26) Kaewnukultorn, Thunchanok; Sepúlveda-Mora, Sergio B.; Hegedus, StevenThe exponential growth of Photovoltaic (PV) technology is creating concerns for electric grid operators. As PV penetration increases, overvoltage in the distribution network can occur due to a mismatch between PV generation and load demand. However, PV smart inverters can be part of the solution to stabilize grid voltage. By providing reactive power and other grid supporting functions, PV inverters in a distribution network can mitigate this problem and enable a higher integration of renewable energy. To accomplish this, characterization and testing of advanced functions must be performed at a small scale before deploying these strategies in the field. In this work, we described in detail the components and communication interfaces of a Hardware-in-the-Loop testbed that includes two 3.8 kW PV inverters from different manufacturers. We conducted efficiency tests on the inverters and characterized the grid supporting functions for grid voltage stabilization, specifically constant power factor, volt-var, and volt-watt. We identified some abnormalities in the operation of the volt-var-watt control in one of the inverters and presented a method to overcome the limitation in remote control of another inverter using Modbus communication. Identifying, understanding, and overcoming shortcomings on the operation of PV smart inverters that provide grid supporting functions is key for the quick adoption of this technology and can help regulatory agencies to determine what is the appropriate control mode that will facilitate higher PV capacity. Additionally, we discuss the economic and technical implications of operating the inverter in active or reactive power grid control.Item Communication-Constrained Routing and Traffic Control: A Framework for Infrastructure-Assisted Autonomous Vehicles(IEEE Transactions on Intelligent Transportation Systems, 2022-09-07) Liu, Guangyi; Salehi, Seyedmohammad; Bala, Erdem; Shen, Chien-Chung; Cimini, Leonard J.With the increasing demand for advanced autonomous driving, the available communication resources may become constrained over different geographic areas. In addition, due to dynamic channel variations and imperfect cell deployments, guaranteeing the required communication resources for data hungry and delay-sensitive applications in autonomous vehicles (AVs), along their entire trips, becomes challenging. To address these issues, the paper investigates the feasibility of a hybrid system-optimum and user-equilibrium AV traffic framework subject to communication constraints, as well as its performance gain. Within such a framework, the paper introduces the problems of communication-constrained routing (CCR) and traffic control (CCTC) in the context of infrastructure-assisted autonomous driving and presents respective solutions. For CCR, an efficient two-layered routing scheme is proposed which can provide optimal trip duration. Simulation results show that the routing scheme achieves a good balance between longer duration of communication coverage and acceptable source-to-destination travel time. For CCTC, it is shown that there exists an optimal AV speed on each road segment, as well as an optimal inter-AV distance and an optimal number of AVs in each cell, to maximize the road-network AV throughput within a single cell. Moreover, spectrum allocation is used to achieve Pareto-optimal road-network throughput across cells, and a new key performance index (KPI) is defined to evaluate the traffic control capability of cellular systems. Simulation results validate the improvement of AV throughput via the proposed CCTC solution.