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Full-Text Articles in Electromagnetics and Photonics

Single-Polarization And Single-Mode Hybrid Hollow-Core Anti-Resonant Fiber Design At 2 Μm, Herschel Herring, Mohammad Al Mahfuz, Md Selim Habib Jun 2024

Single-Polarization And Single-Mode Hybrid Hollow-Core Anti-Resonant Fiber Design At 2 Μm, Herschel Herring, Mohammad Al Mahfuz, Md Selim Habib

Electrical Engineering and Computer Science Faculty Publications

In this paper, to the best of our knowledge, a new
type of hollow-core anti-resonant fiber (HC-ARF) design using
hybrid silica/high-index material (HIM) cladding is presented
for single-polarization, high-birefringence, and endlessly single-
mode operation at 2 μm wavelength. We show that the inclusion
of a HIM layer in the cladding allows strong suppression of
𝑥−polarization, while maintaining low propagation loss and
single-mode propagation for 𝑦−polarization. The optimized HC-
ARF design includes a combination of low propagation loss,
high-birefringence, and polarization-extinction ratio (PER) or
loss ratio of 0.02 dB/m, 1.2×10−4, and >550 respectively, while the
loss of the 𝑥−polarization is >20 …


6d Single-Fluorogen Orientation-Localization Microscopy For Elucidating The Architecture Of Beta-Sheet Assemblies And Biomolecular Condensates, Tingting Wu, Weiyan Zhou, Jai S. Rudra, Rohit V. Pappu, Matthew D. Lew Mar 2024

6d Single-Fluorogen Orientation-Localization Microscopy For Elucidating The Architecture Of Beta-Sheet Assemblies And Biomolecular Condensates, Tingting Wu, Weiyan Zhou, Jai S. Rudra, Rohit V. Pappu, Matthew D. Lew

Electrical & Systems Engineering Publications and Presentations

We develop six-dimensional single-molecule orientation-localization microscopy (SMOLM) to measure the 3D positions and 3D orientations simultaneously of single fluorophores. We show how careful optimization of phase and polarization modulation components can encode phase, polarization, and angular spectrum information from each fluorescence photon into a microscope’s dipole-spread function. We used the transient binding and blinking of Nile red (NR) to characterize the helical structure of fibrils formed by designed amphipathic peptides, KFE8L and KFE8D, and the pathological amyloid-beta peptide Aβ42. We also deployed merocyanine 540 to uncover the interfacial architectures of biomolecular condensates.


Tailored Micromagnet Sorting Gate For Simultaneous Multiple Cell Screening In Portable Magnetophoretic Cell-On-Chip Platforms, Jonghwan Yoon, Yumin Kang, Hyeonseol Kim, Abbas Ali, Keonmok Kim, Sri Ramulu Torati, Mi-Young Im, Changyeop Jeon, Byeonghwa Lim, Cheolgi Kim Jan 2024

Tailored Micromagnet Sorting Gate For Simultaneous Multiple Cell Screening In Portable Magnetophoretic Cell-On-Chip Platforms, Jonghwan Yoon, Yumin Kang, Hyeonseol Kim, Abbas Ali, Keonmok Kim, Sri Ramulu Torati, Mi-Young Im, Changyeop Jeon, Byeonghwa Lim, Cheolgi Kim

Bioelectronics Publications

Conventional magnetophoresis techniques for manipulating biocarriers and cells predominantly rely on large-scale electromagnetic systems, which is a major obstacle to the development of portable and miniaturized cell-on-chip platforms. Herein, a novel magnetic engineering approach by tailoring a nanoscale notch on a disk micromagnet using two-step optical and thermal lithography is developed. Versatile manipulations are demonstrated, such as separation and trapping, of carriers and cells by mediating changes in the magnetic domain structure and discontinuous movement of magnetic energy wells around the circumferential edge of the micromagnet caused by a locally fabricated nano-notch in a low magnetic field system. The motion …


Photoluminescence Switching In Quantum Dots Connected With Fluorinated And Hydrogenated Photochromic Molecules, Ephraiem S. Sarabamoun, Jonathan M. Bietsch, Pramod Aryal, Amelia G. Reid, Maurice Curran, Grayson Johnson, Esther H. R. Tsai, Charles W. Machan, Guijun Wang, Joshua J. Choi Jan 2024

Photoluminescence Switching In Quantum Dots Connected With Fluorinated And Hydrogenated Photochromic Molecules, Ephraiem S. Sarabamoun, Jonathan M. Bietsch, Pramod Aryal, Amelia G. Reid, Maurice Curran, Grayson Johnson, Esther H. R. Tsai, Charles W. Machan, Guijun Wang, Joshua J. Choi

Chemistry & Biochemistry Faculty Publications

We investigate switching of photoluminescence (PL) from PbS quantum dots (QDs) crosslinked with two different types of photochromic diarylethene molecules, 4,4'-(1-cyclopentene-1,2-diyl)bis[5-methyl-2-thiophenecarboxylic acid] (1H) and 4,4'-(1-perfluorocyclopentene-1,2-diyl)bis[5-methyl-2-thiophenecarboxylic acid] (2F). Our results show that the QDs crosslinked with the hydrogenated molecule (1H) exhibit a greater amount of switching in photoluminescence intensity compared to QDs crosslinked with the fluorinated molecule (2F). With a combination of differential pulse voltammetry and density functional theory, we attribute the different amount of PL switching to the different energy levels between 1H and 2F molecules which result in different potential barrier …


Exponential Fusion Of Interpolated Frames Network (Efif-Net): Advancing Multi-Frame Image Super-Resolution With Convolutional Neural Networks, Hamed Elwarfalli, Dylan Flaute, Russell C. Hardie Jan 2024

Exponential Fusion Of Interpolated Frames Network (Efif-Net): Advancing Multi-Frame Image Super-Resolution With Convolutional Neural Networks, Hamed Elwarfalli, Dylan Flaute, Russell C. Hardie

Electrical and Computer Engineering Faculty Publications

Convolutional neural networks (CNNs) have become instrumental in advancing multi-frame image super-resolution (SR), a technique that merges multiple low-resolution images of the same scene into a high-resolution image. In this paper, a novel deep learning multi-frame SR algorithm is introduced. The proposed CNN model, named Exponential Fusion of Interpolated Frames Network (EFIF-Net), seamlessly integrates fusion and restoration within an end-to-end network. Key features of the new EFIF-Net include a custom exponentially weighted fusion (EWF) layer for image fusion and a modification of the Residual Channel Attention Network for restoration to deblur the fused image. Input frames are registered with subpixel …


Intelligent Millimeter-Wave System For Human Activity Monitoring For Telemedicine, Abdullah K. Alhazmi, Mubarak A. Alanazi, Awwad H. Alshehry, Saleh M. Alshahry, Jennifer Jaszek, Cameron Djukic, Anna Brown, Kurt Jackson, Vamsy P. Chodavarapu Jan 2024

Intelligent Millimeter-Wave System For Human Activity Monitoring For Telemedicine, Abdullah K. Alhazmi, Mubarak A. Alanazi, Awwad H. Alshehry, Saleh M. Alshahry, Jennifer Jaszek, Cameron Djukic, Anna Brown, Kurt Jackson, Vamsy P. Chodavarapu

Electrical and Computer Engineering Faculty Publications

Telemedicine has the potential to improve access and delivery of healthcare to diverse and aging populations. Recent advances in technology allow for remote monitoring of physiological measures such as heart rate, oxygen saturation, blood glucose, and blood pressure. However, the ability to accurately detect falls and monitor physical activity remotely without invading privacy or remembering to wear a costly device remains an ongoing concern. Our proposed system utilizes a millimeter-wave (mmwave) radar sensor (IWR6843ISK-ODS) connected to an NVIDIA Jetson Nano board for continuous monitoring of human activity. We developed a PointNet neural network for real-time human activity monitoring that can …


Directional Microwave Emission From Femtosecond-Laser Illuminated Linear Arrays Of Superconducting Rings, Thomas J. Bullard, Kyle Frische, Charlie Ebbing, Stephen J. Hageman, John Morrison, John Bulmer, Enam A. Chowdury, Michael L. Dexter, Timothy J. Haugan, Anil K. Patniak Dec 2023

Directional Microwave Emission From Femtosecond-Laser Illuminated Linear Arrays Of Superconducting Rings, Thomas J. Bullard, Kyle Frische, Charlie Ebbing, Stephen J. Hageman, John Morrison, John Bulmer, Enam A. Chowdury, Michael L. Dexter, Timothy J. Haugan, Anil K. Patniak

Faculty Publications

We examine the electromagnetic emission from two photo-illuminated linear arrays composed of inductively charged superconducting ring elements. The arrays are illuminated by an ultrafast infrared laser that triggers microwave broadband emission detected in the 1–26 GHz range. Based on constructive interference from the arrays a narrowing of the forward radiation lobe is observed with increasing element count and frequency demonstrating directed GHz emission. Results suggest that higher frequencies and a larger number of elements are achievable leading to a unique pulsed array emitter concept that can span frequencies from the microwave to the terahertz (THz) regime.


Adaptive Plasmonic Metasurfaces For Radiative Cooling And Passive Thermoregulation, Azadeh Didari-Bader, Nooshin M. Estakhri, Nasim Mohammadi Estrakhri Jun 2023

Adaptive Plasmonic Metasurfaces For Radiative Cooling And Passive Thermoregulation, Azadeh Didari-Bader, Nooshin M. Estakhri, Nasim Mohammadi Estrakhri

Engineering Faculty Articles and Research

In this work, we investigate a class of planar photonic structures operating as passive thermoregulators. The radiative cooling process is adjusted through the incorporation of a phase change material (Vanadium Dioxide, VO2) in conjunction with a layer of transparent conductive oxide (Aluminum-doped Zinc Oxide, AZO). VO2 is known to undergo a phase transition from the “dielectric” phase to the “plasmonic” or “metallic” phase at a critical temperature close to 68°C. In addition, AZO shows plasmonic properties at the long-wave infrared spectrum, which, combined with VO2, provides a rich platform to achieve low reflections across the …


Effect On Focusing Fields By Ferromagnetic Cell Cores In Linear Induction Accelerators, Cooper Guillaume May 2023

Effect On Focusing Fields By Ferromagnetic Cell Cores In Linear Induction Accelerators, Cooper Guillaume

Senior Honors Theses

In the Los Alamos National Laboratories DARHT facility, there are two perpendicular linear induction accelerators, LIAs. The LIAs’ solenoids produce magnetic fields which focus the electron beam. Simultaneously, the accelerating pulse creates a magnetic field. These two field intensities act upon a ferromagnetic material in the cells to enhance magnetic flux density. Due to the nonlinearity of the material, this flux density will reach a saturation point. In turn, the magnetic field intensity of the axial solenoidal magnetic field will be affected and slightly altered. The width of the electron beam will increase, causing a decrease in effectiveness. Through simulation, …


Implementing Commercial Inverse Design Tools For Compact, Phase-Encoded, Plasmonic Digital Logic Devices, Michael Efseaff, Kyle Wynne, Krishna Narayan, Mark C. Harrison Mar 2023

Implementing Commercial Inverse Design Tools For Compact, Phase-Encoded, Plasmonic Digital Logic Devices, Michael Efseaff, Kyle Wynne, Krishna Narayan, Mark C. Harrison

Engineering Faculty Articles and Research

Numerical simulations have become an essential design tool in the field of photonics, especially for nanophotonics. In particular, 3D finite-difference-time-domain (FDTD) simulations are popular for their powerful design capabilities. Increasingly, researchers are developing or using inverse design tools to improve device footprints and performance. These tools often make use of 3D FDTD simulations and the adjoint optimization method. We implement a commercial inverse design tool with these features for several plasmonic devices that push the boundaries of the tool. We design a logic gate with complex design requirements as well as a y-splitter and waveguide crossing. With minimal code changes, …


Evolution Of Coronal Magnetic Field Parameters During X5.4 Solar Flare, Seth H. Garland, Benjamin F. Akers, Vasyl B. Yurchyshyn, Robert D. Loper, Daniel J. Emmons Mar 2023

Evolution Of Coronal Magnetic Field Parameters During X5.4 Solar Flare, Seth H. Garland, Benjamin F. Akers, Vasyl B. Yurchyshyn, Robert D. Loper, Daniel J. Emmons

Faculty Publications

The coronal magnetic field over NOAA Active Region 11,429 during a X5.4 solar flare on 7 March 2012 is modeled using optimization based Non-Linear Force-Free Field extrapolation. Specifically, 3D magnetic fields were modeled for 11 timesteps using the 12-min cadence Solar Dynamics Observatory (SDO) Helioseismic and Magnetic Imager photospheric vector magnetic field data, spanning a time period of 1 hour before through 1 hour after the start of the flare. Using the modeled coronal magnetic field data, seven different magnetic field parameters were calculated for 3 separate regions: areas with surface |Bz| ≥ 300 G, areas of flare brightening seen …


Electromagnetic Transmit Array With Optical Control For Beamforming, Wei Zhang, Javad Meiguni, Yin Sun, Muqi Ouyang, Xin Yan, Xu Wang, Reza Yazdani, Daryl G. Beetner, Donghyun Kim, David Pommerenke Jan 2023

Electromagnetic Transmit Array With Optical Control For Beamforming, Wei Zhang, Javad Meiguni, Yin Sun, Muqi Ouyang, Xin Yan, Xu Wang, Reza Yazdani, Daryl G. Beetner, Donghyun Kim, David Pommerenke

Electrical and Computer Engineering Faculty Research & Creative Works

This Proof-Of-Concept Paper Demonstrates the Feasibility of using a Slide Projector to Steer the Beam of a Transmit Array by Adding Solar Cells and Varactor Diodes to Each Unit Cell. by Irradiating Each Solar Cell with the Light of Different Intensities from a Slide Projector, the Measured Phase of the Wave Transmitted by the 4x4 Transmit Array Shifts within 92° at 4.26 GHz, While the Variation in Magnitude is Measured within 4 DB. Different Light Configurations Are Identified Via a Searching Algorithm to Achieve Peak/null Beamforming in a Particular Direction. the Beam of the Prototypical 4x4 Transmit Array Can Be …


Methodology For Analyzing Coupling Mechanisms In Rfi Problems Based On Peec, Xu Wang, Anfeng Huang, Wei Zhang, Reza Yazdani, Donghyun Kim, Takashi Enomoto, Taketoshi Sekine, Kenji Araki, Jun Fan, Chulsoon Hwang Jan 2023

Methodology For Analyzing Coupling Mechanisms In Rfi Problems Based On Peec, Xu Wang, Anfeng Huang, Wei Zhang, Reza Yazdani, Donghyun Kim, Takashi Enomoto, Taketoshi Sekine, Kenji Araki, Jun Fan, Chulsoon Hwang

Electrical and Computer Engineering Faculty Research & Creative Works

In This Article, a Method for Analyzing Coupling Mechanisms in Radio Frequency Interference (RFI) Problems is Proposed. the Partial Element Equivalent Circuit (PEEC) Method is First Used to Derive the Retarded Inductances and Capacitances between Different Mesh Cells. with the Introduction of a Novel Partitioning Algorithm, the Capacitive Coupling and Inductive Coupling between Arbitrary Layout Parts Can Be Quantified based on the Magnitude of the Displacement Current and Induced Voltage Drop. the Accuracy of the PEEC Models is Validated by Comparison with Different Commercial Tools. the Proposed Coupling Mechanism Analysis Flow Provides a Useful Prelayout Tool for RFI Risk Analysis.


The Effect Of The Width Of The Incident Pulse To The Dielectric Transition Layer In The Scattering Of An Electromagnetic Pulse — A Qubit Lattice Algorithm Simulation, George Vahala, Linda Vahala, Abhay K. Ram, Min Soe Jan 2023

The Effect Of The Width Of The Incident Pulse To The Dielectric Transition Layer In The Scattering Of An Electromagnetic Pulse — A Qubit Lattice Algorithm Simulation, George Vahala, Linda Vahala, Abhay K. Ram, Min Soe

Electrical & Computer Engineering Faculty Publications

The effect of the thickness of the dielectric boundary layer that connects a material of refractive index n1 to another of index n2is considered for the propagation of an electromagnetic pulse. A qubit lattice algorithm (QLA), which consists of a specially chosen non-commuting sequence of collision and streaming operators acting on a basis set of qubits, is theoretically determined that recovers the Maxwell equations to second-order in a small parameter ϵ. For very thin boundary layer the scattering properties of the pulse mimics that found from the Fresnel jump conditions for a plane wave - except that …


Emergence Of Coherent Backscattering From Sparse And Finite Disordered Media, Nooshin M. Estakhri, Nasim Mohammadi Estrakhri, Theodore B. Norris Dec 2022

Emergence Of Coherent Backscattering From Sparse And Finite Disordered Media, Nooshin M. Estakhri, Nasim Mohammadi Estrakhri, Theodore B. Norris

Engineering Faculty Articles and Research

Coherent backscattering (CBS) arises from complex interactions of a coherent beam with randomly positioned particles, which has been typically studied in media with large numbers of scatterers and high opacity. We develop a first-principles scattering model for scalar waves to study the CBS cone formation in finite-sized and sparse random media with specific geometries. The current study provides insights into the effects of density, volume size, and other relevant parameters on the angular characteristics of the CBS cone emerging from sparse and bounded random media for various types of illumination, with results consistent with well-known CBS studies which are typically …


Six-Dimensional Single-Molecule Imaging With Isotropic Resolution Using A Multi-View Reflector Microscope, Oumeng Zhang, Zijian Guo, Yuanyuan He, Tingting Wu, Michael D. Vahey, Matthew D. Lew Dec 2022

Six-Dimensional Single-Molecule Imaging With Isotropic Resolution Using A Multi-View Reflector Microscope, Oumeng Zhang, Zijian Guo, Yuanyuan He, Tingting Wu, Michael D. Vahey, Matthew D. Lew

Electrical & Systems Engineering Publications and Presentations

Imaging of both the positions and orientations of single fluorophores, termed single-molecule orientation-localization microscopy, is a powerful tool for the study of biochemical processes. However, the limited photon budget associated with single-molecule fluorescence makes high-dimensional imaging with isotropic, nanoscale spatial resolution a formidable challenge. Here we realize a radially and azimuthally polarized multi-view reflector (raMVR) microscope for the imaging of the three-dimensional (3D) positions and 3D orientations of single molecules, with precisions of 10.9 nm and 2.0° over a 1.5-μm depth range. The raMVR microscope achieves 6D super-resolution imaging of Nile red molecules transiently bound to lipid-coated spheres, accurately resolving …


A Patient-Specific Algorithm For Lung Segmentation In Chest Radiographs, Manawaduge Supun De Silva, Barath Narayanan Narayanan, Russell C. Hardie Nov 2022

A Patient-Specific Algorithm For Lung Segmentation In Chest Radiographs, Manawaduge Supun De Silva, Barath Narayanan Narayanan, Russell C. Hardie

Electrical and Computer Engineering Faculty Publications

Lung segmentation plays an important role in computer-aided detection and diagnosis using chest radiographs (CRs). Currently, the U-Net and DeepLabv3+ convolutional neural network architectures are widely used to perform CR lung segmentation. To boost performance, ensemble methods are often used, whereby probability map outputs from several networks operating on the same input image are averaged. However, not all networks perform adequately for any specific patient image, even if the average network performance is good. To address this, we present a novel multi-network ensemble method that employs a selector network. The selector network evaluates the segmentation outputs from several networks; on …


Electro-Optical Sensors For Atmospheric Turbulence Strength Characterization With Embedded Edge Ai Processing Of Scintillation Patterns, Ernst Polnau, Don L. N. Hettiarachchi, Mikhail A. Vorontsov Oct 2022

Electro-Optical Sensors For Atmospheric Turbulence Strength Characterization With Embedded Edge Ai Processing Of Scintillation Patterns, Ernst Polnau, Don L. N. Hettiarachchi, Mikhail A. Vorontsov

Electro-Optics and Photonics Faculty Publications

This study introduces electro-optical (EO) sensors (TurbNet sensors) that utilize a remote laser beacon (either coherent or incoherent) and an optical receiver with CCD camera and embedded edge AI computer (Jetson Xavier Nx) for in situ evaluation of the path-averaged atmospheric turbulence refractive index structure parameter C-n(2) at a high temporal rate. Evaluation of C-n(2) values was performed using deep neural network (DNN)-based real-time processing of short-exposure laser-beacon light intensity scintillation patterns (images) captured by a TurbNet sensor optical receiver. Several pre-trained DNN models were loaded onto the AI computer and used for TurbNet sensor performance evaluation in a set …


Arrayed Waveguide Lens For Beam Steering, Mostafa Honari-Latifpour, Ali Binaie, Mohammad Amin Eftekhar, Nicholas Madamopoulos, Mohammad-Ali Miri Aug 2022

Arrayed Waveguide Lens For Beam Steering, Mostafa Honari-Latifpour, Ali Binaie, Mohammad Amin Eftekhar, Nicholas Madamopoulos, Mohammad-Ali Miri

Publications and Research

Integrated planar lenses are critical components for analog optical information processing that enable a wide range of applications including beam steering. Conventional planar lenses require gradient index control which makes their on-chip realization challenging. Here, we introduce a new approach for beam steering by designing an array of coupled waveguides with segmented tails that allow for simultaneously achieving planar lensing and off-chip radiation. The proposed arrayed waveguide lens is built on engineering the evanescent coupling between adjacent channels to realize a photonic lattice with an equi-distant ladder of propagation constants that emulates the continuous parabolic index profile. Through coupled-mode analysis …


Glaciernet2: A Hybrid Multi-Model Learning Architecture For Alpine Glacier Mapping, Zhiyuan Xie, Umesh K. Haritashya, Vijayan K. Asari, Michael P. Bishop, Jeffrey S. Kargel, Theus Aspiras Aug 2022

Glaciernet2: A Hybrid Multi-Model Learning Architecture For Alpine Glacier Mapping, Zhiyuan Xie, Umesh K. Haritashya, Vijayan K. Asari, Michael P. Bishop, Jeffrey S. Kargel, Theus Aspiras

Electrical and Computer Engineering Faculty Publications

In recent decades, climate change has significantly affected glacier dynamics, resulting in mass loss and an increased risk of glacier-related hazards including supraglacial and proglacial lake development, as well as catastrophic outburst flooding. Rapidly changing conditions dictate the need for continuous and detailed ob-servations and analysis of climate-glacier dynamics. Thematic and quantitative information regarding glacier geometry is fundamental for understanding climate forcing and the sensitivity of glaciers to climate change, however, accurately mapping debris-cover glaciers (DCGs) is notoriously difficult based upon the use of spectral information and conventional machine-learning techniques. The objective of this research is to improve upon an …


Towards A Low-Cost Solution For Gait Analysis Using Millimeter Wave Sensor And Machine Learning, Mubarak A. Alanazi, Abdullah K. Alhazmi, Osama Alsattam, Kara Gnau, Meghan Brown, Shannon Thiel, Kurt Jackson, Vamsy P. Chodavarapu Aug 2022

Towards A Low-Cost Solution For Gait Analysis Using Millimeter Wave Sensor And Machine Learning, Mubarak A. Alanazi, Abdullah K. Alhazmi, Osama Alsattam, Kara Gnau, Meghan Brown, Shannon Thiel, Kurt Jackson, Vamsy P. Chodavarapu

Electrical and Computer Engineering Faculty Publications

Human Activity Recognition (HAR) that includes gait analysis may be useful for various rehabilitation and telemonitoring applications. Current gait analysis methods, such as wearables or cameras, have privacy and operational constraints, especially when used with older adults. Millimeter-Wave (MMW) radar is a promising solution for gait applications because of its low-cost, better privacy, and resilience to ambient light and climate conditions. This paper presents a novel human gait analysis method that combines the micro-Doppler spectrogram and skeletal pose estimation using MMW radar for HAR. In our approach, we used the Texas Instruments IWR6843ISK-ODS MMW radar to obtain the micro-Doppler spectrogram …


Novel Materials And Devices For Terahertz Detection And Emission For Sensing, Imaging And Communication, Naznin Akter Jun 2022

Novel Materials And Devices For Terahertz Detection And Emission For Sensing, Imaging And Communication, Naznin Akter

FIU Electronic Theses and Dissertations

Technical advancement is required to attain a high data transmission rate, which entails expanding beyond the currently available bandwidth and establishing a new standard for the highest data rates, which mandates a higher frequency range and larger bandwidth. The THz spectrum (0.1-10 THz) has been considered as an emerging next frontier for the future 5G and beyond technology. THz frequencies also offer unique characteristics, such as penetrating most dielectric materials like fabric, plastic, and leather, making them appealing for imaging and sensing applications. Therefore, employing a high-power room temperature, tunable THz emitters, and a high responsivity THz detector is essential. …


Imnets: Deep Learning Using An Incremental Modular Network Synthesis Approach For Medical Imaging Applications, Redha A. Ali, Russell C. Hardie, Barath Narayanan Narayanan, Temesguen Messay Jun 2022

Imnets: Deep Learning Using An Incremental Modular Network Synthesis Approach For Medical Imaging Applications, Redha A. Ali, Russell C. Hardie, Barath Narayanan Narayanan, Temesguen Messay

Electrical and Computer Engineering Faculty Publications

Deep learning approaches play a crucial role in computer-aided diagnosis systems to support clinical decision-making. However, developing such automated solutions is challenging due to the limited availability of annotated medical data. In this study, we proposed a novel and computationally efficient deep learning approach to leverage small data for learning generalizable and domain invariant representations in different medical imaging applications such as malaria, diabetic retinopathy, and tuberculosis. We refer to our approach as Incremental Modular Network Synthesis (IMNS), and the resulting CNNs as Incremental Modular Networks (IMNets). Our IMNS approach is to use small network modules that we call SubNets …


Sub-Nyquist Optical Pulse Sampling For Photonic Blind Source Separation, Taichu Shi, Yang Qi, Weipeng Zhang, Paul Prucnal, Jie Li, Ben Wu May 2022

Sub-Nyquist Optical Pulse Sampling For Photonic Blind Source Separation, Taichu Shi, Yang Qi, Weipeng Zhang, Paul Prucnal, Jie Li, Ben Wu

Henry M. Rowan College of Engineering Faculty Scholarship

We propose and experimentally demonstrate an optical pulse sampling method for photonic blind source separation. The photonic system processes and separates wideband signals based on the statistical information of the mixed signals, and thus the sampling frequency can be orders of magnitude lower than the bandwidth of the signals. The ultra-fast optical pulses collect samples of the signals at very low sampling rates, and each sample is short enough to maintain the statistical properties of the signals. The low sampling frequency reduces the workloads of the analog to digital conversion and digital signal processing systems. In the meantime, the short …


Microscopic Nuclei Classification, Segmentation, And Detection With Improved Deep Convolutional Neural Networks (Dcnn), Md Zahangir Alom, Vijayan K. Asari, Anil Parwani, Tarek M. Taha Apr 2022

Microscopic Nuclei Classification, Segmentation, And Detection With Improved Deep Convolutional Neural Networks (Dcnn), Md Zahangir Alom, Vijayan K. Asari, Anil Parwani, Tarek M. Taha

Electrical and Computer Engineering Faculty Publications

Background Nuclei classification, segmentation, and detection from pathological images are challenging tasks due to cellular heterogeneity in the Whole Slide Images (WSI). Methods In this work, we propose advanced DCNN models for nuclei classification, segmentation, and detection tasks. The Densely Connected Neural Network (DCNN) and Densely Connected Recurrent Convolutional Network (DCRN) models are applied for the nuclei classification tasks. The Recurrent Residual U-Net (R2U-Net) and the R2UNet-based regression model named the University of Dayton Net (UD-Net) are applied for nuclei segmentation and detection tasks respectively. The experiments are conducted on publicly available datasets, including Routine Colon Cancer (RCC) classification and …


Towards Improved Inertial Navigation By Reducing Errors Using Deep Learning Methodology, Hua Chen, Tarek M. Taha, Vamsy P. Chodavarapu Apr 2022

Towards Improved Inertial Navigation By Reducing Errors Using Deep Learning Methodology, Hua Chen, Tarek M. Taha, Vamsy P. Chodavarapu

Electrical and Computer Engineering Faculty Publications

Autonomous vehicles make use of an Inertial Navigation System (INS) as part of vehicular sensor fusion in many situations including GPS-denied environments such as dense urban places, multi-level parking structures, and areas with thick tree-coverage. The INS unit incorporates an Inertial Measurement Unit (IMU) to process the linear acceleration and angular velocity data to obtain orientation, position, and velocity information using mechanization equations. In this work, we describe a novel deep-learning-based methodology, using Convolutional Neural Networks (CNN), to reduce errors from MEMS IMU sensors. We develop a CNN-based approach that can learn from the responses of a particular inertial sensor …


Polarization-Sensitive Optical Responses From Natural Layered Hydrated Sodium Sulfosalt Gerstleyite, Ravi P. N. Tripathi, Xiaodong Yang, Jie Gao Mar 2022

Polarization-Sensitive Optical Responses From Natural Layered Hydrated Sodium Sulfosalt Gerstleyite, Ravi P. N. Tripathi, Xiaodong Yang, Jie Gao

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Multi-element layered materials have gained substantial attention in the context of achieving the customized light-matter interactions at subwavelength scale via stoichiometric engineering, which is crucial for the realization of miniaturized polarization-sensitive optoelectronic and nanophotonic devices. Herein, naturally occurring hydrated sodium sulfosalt gerstleyite is introduced as one new multi-element van der Waals (vdW) layered material. The mechanically exfoliated thin gerstleyite flakes are demonstrated to exhibit polarization-sensitive anisotropic linear and nonlinear optical responses including angle-resolved Raman scattering, anomalous wavelength-dependent linear dichroism transition, birefringence effect, and polarization-dependent third-harmonic generation (THG). Furthermore, the third-order nonlinear susceptibility of gerstleyite crystal is estimated by the probed …


Resolving The Three-Dimensional Rotational And Translational Dynamics Of Single Molecules Using Radially And Azimuthally Polarized Fluorescence, Oumeng Zhang, Weiyan Zhou, Jin Lu, Tingting Wu, Matthew D. Lew Jan 2022

Resolving The Three-Dimensional Rotational And Translational Dynamics Of Single Molecules Using Radially And Azimuthally Polarized Fluorescence, Oumeng Zhang, Weiyan Zhou, Jin Lu, Tingting Wu, Matthew D. Lew

Electrical & Systems Engineering Publications and Presentations

We report a radially and azimuthally polarized (raPol) microscope for high detection and estimation performance in single-molecule orientation-localization microscopy (SMOLM). With 5000 photons detected from Nile red (NR) transiently bound within supported lipid bilayers (SLBs), raPol SMOLM achieves 2.9 nm localization precision, 1.5° orientation precision, and 0.17 sr precision in estimating rotational wobble. Within DPPC SLBs, SMOLM imaging reveals the existence of randomly oriented binding pockets that prevent NR from freely exploring all orientations. Treating the SLBs with cholesterol-loaded methyl-β-cyclodextrin (MβCD-chol) causes NR’s orientational diffusion to be dramatically reduced, but curiously NR’s median lateral displacements drastically increase from 20.8 to …


Characteristic Mode Analysis Prediction And Guidance Of Electromagnetic Coupling Measurements To A Uav Model, Mohamed Z. M. Hamdalla, Benjamin Bissen, James D. Hunter, Yuanzhuo Liu, Victor Khilkevich, Daryl G. Beetner, Anthony N. Caruso, Ahmed M. Hassan Jan 2022

Characteristic Mode Analysis Prediction And Guidance Of Electromagnetic Coupling Measurements To A Uav Model, Mohamed Z. M. Hamdalla, Benjamin Bissen, James D. Hunter, Yuanzhuo Liu, Victor Khilkevich, Daryl G. Beetner, Anthony N. Caruso, Ahmed M. Hassan

Electrical and Computer Engineering Faculty Research & Creative Works

In this work, we study the current coupled to a simplified Unmanned Aerial Vehicle (UAV) model using a dual computational and experimental approach. The simplified surrogate structure reduced the computational burden and facilitated the experimental measurement of the coupled currents. For a practical system, a wide range of simulations and measurements must be performed to analyze the induced current variations with respect to properties of the incident excitation waveform, such as the frequency, angle of incidence, and polarization. To simplify this analysis, Characteristic Mode Analysis (CMA) was used to compute the eigen-currents of the UAV model and predict where and …


A Deep Neural Network For Early Detection And Prediction Of Chronic Kidney Disease, Vijendra Singh, Vijayan K. Asari, Rajkumar Rajasekaran Jan 2022

A Deep Neural Network For Early Detection And Prediction Of Chronic Kidney Disease, Vijendra Singh, Vijayan K. Asari, Rajkumar Rajasekaran

Electrical and Computer Engineering Faculty Publications

Diabetes and high blood pressure are the primary causes of Chronic Kidney Disease (CKD). Glomerular Filtration Rate (GFR) and kidney damage markers are used by researchers around the world to identify CKD as a condition that leads to reduced renal function over time. A person with CKD has a higher chance of dying young. Doctors face a difficult task in diagnosing the different diseases linked to CKD at an early stage in order to prevent the disease. This research presents a novel deep learning model for the early detection and prediction of CKD. This research objectives to create a deep …