Optics Commons^™

Ev Charging Behavior Analysis Using Hybrid Intelligence For 5g Smart Grid, Yi Shen, Wei Fang, Feng Ye, Michel Kadoch

Electrical and Computer Engineering Faculty Publications

With the development of the Internet of Things (IoT) and the widespread use of electric vehicles (EV), vehicle-to-grid (V2G) has sparked considerable discussion as an energy-management technology. Due to the inherently high maneuverability of EVs, V2G systems must provide on-demand service for EVs. Therefore, in this work, we propose a hybrid computing architecture based on fog and cloud with applications in 5G-based V2G networks. This architecture allows the bi-directional flow of power and information between schedulable EVs and smart grids (SGs) to improve the quality of service and cost-effectiveness of energy service providers. However, it is very important to select …

Glaciernet: A Deep-Learning Approach For Debris-Covered Glacier Mapping, Zhiyuan Xie, Umesh K. Haritashya, Vijayan K. Asari, Brennan W. Young, Michael P. Bishop, Jeffrey S. Kargel

Electrical and Computer Engineering Faculty Publications

Rising global temperatures over the past decades is directly affecting glacier dynamics. To understand glacier fluctuations and document regional glacier-state trends, glacier-boundary detection is necessary. Debris-covered glacier (DCG) mapping, however, is notoriously difficult using conventional geospatial technology methods. Therefore, in this research for automated DCG mapping, we evaluate the utility of a convolutional neural network (CNN), which is a deep learning feed-forward neural network. The CNN inputs include Landsat satellite images, an Advanced Land Observation Satellite (ALOS) digital elevation model (DEM) and DEM-derived land-surface parameters. Our CNN based deep-learning approach named GlacierNet was designed by appropriately choosing the type, number …

Mitosisnet: End-To-End Mitotic Cell Detection By Multi-Task Learning, Md Zahangir Alom, Theus Aspiras, Tarek M. Taha, Tj Bowen, Vijayan K. Asari

Electrical and Computer Engineering Faculty Publications

Mitotic cell detection is one of the challenging problems in the field of computational pathology. Currently, mitotic cell detection and counting are one of the strongest prognostic markers for breast cancer diagnosis. The clinical visual inspection on histology slides is tedious, error prone, and time consuming for the pathologist. Thus, automatic mitotic cell detection approaches are highly demanded in clinical practice. In this paper, we propose an end-to-end multi-task learning system for mitosis detection from pathological images which is named"MitosisNet". MitosisNet consist of segmentation, detection, and classification models where the segmentation, and detection models are used for mitosis reference region …

Independent And Simultaneous Control Of Electromagnetic Wave Properties In Self-Collimating Photonic Crystals Using Spatial Variance, Jesus Javier Gutierrez

Open Access Theses & Dissertations

Photonic crystals are engineered periodic structures that provide great control over electromagnetic waves. One of these mechanisms is self-collimation, in which the electromagnetic wave travels through the photonic crystal along an axis of the lattice without diffracting or spreading. This mechanism of self-collimation is a dispersion phenomenon, which is dependent on the unit cell's physical and geometrical characteristics. An algorithm for generating spatially variant lattices (SVL) was developed that can change geometrical properties in photonic crystals as a function of position, like unit cell orientation, fill fraction, symmetry, and others in a manner that is smooth, continuous, and virtually free …

Parallelized X-Ray Tracing With Gpu Ray-Tracing Engine, Joseph Ulseth

Electronic Theses and Dissertations, 2020-2023

X-ray diffraction tomography (XDT) is used to probe material composition of objects, providing improved contrast between materials compared to conventional transmission based computed tomography (CT). In this work, a small angle approximation to Bragg's Equation of diffraction is coupled with parallelized computing using Graphics Processing Units (GPUs) to accelerate XDT simulations. The approximation gives rise to a simple yet useful proportionality between momentum transfer, radial distance of diffracted signal with respect to incoming beam's location, and depth of material, so that ray tracing may be parallelized. NVIDIA's OptiX ray-tracing engine, a parallelized pipeline for GPUs, is employed to perform XDT …

Fluorescence Microscopy With Tailored Illumination Light, Jialei Tang

Electronic Theses and Dissertations, 2020-2023

Fluorescence microscopy has long been a valuable tool for biological and medical imaging. Control of optical parameters such as the amplitude, phase, polarization and propagation angle of light gives fluorescence imaging great capabilities ranging from single molecule imaging to long-term observation of living organisms. While numerous fluorescence imaging techniques have been developed over the past decades, there is always an inevitable tradeoff among the spatial resolution, imaging speed, contrast, photodamage and the total cost when it comes to choose the appropriate microscope. A main goal of my dissertation research is to develop state-of-the-art microscope systems that exhibit unprecedented performance in …

Nonlinear Optical Mechanisms In Semiconductors And Enhanced Nonlinearities At Epsilon-Near-Zero, Sepehr Ahmadzadeh Benis

Electronic Theses and Dissertations, 2020-2023

Light does not interact with itself in linear optical materials. Such interactions occur only in non-linear optical (NLO) materials and typically require high intensity optical beams to be signifi-cant. The ever-increasing role of NLO, where intense light may change the properties of the me-dium, has created a pressing demand to invent materials for achieving more efficient light-light and light-matter interaction due to their potential capacity to augment and possibly replace cur-rent technologies with more efficient devices. There are numerous applications of NLO devices in fundamental science, technology, health, and defense such as all-optical computation and sig-nal processing, ultrashort laser technology, …

Iterative Optical Diffraction Tomography For Reconstruction Of Multiply-Scattering Objects, Shengli Fan

Electronic Theses and Dissertations, 2020-2023

As a label-free, non-destructive, high-resolution, and quantitative imaging technique, optical diffraction tomography (ODT) has been widely used to image biological samples and microstructures, such as cells, tissues, and optical fibers. The refractive-index (RI) distribution of an object is reconstructed from multi-view measurements of diffracted fields emerging from the object. Typical ODT setups include the object rotating configuration (ORC) and the illumination scanning configuration (ISC). One major limitation of ODT is that it is only applicable to weakly-scattering objects. In this dissertation, novel methods have been developed to overcome the reconstruction difficulty caused by multiple scattering, so as to extend ODT …

Investigation Of Phonon Polaritons In An Hbn Gan Heterostructure, Catherine G. O'Hearn

Graduate Theses, Dissertations, and Problem Reports (ETD)

There have been many great advances in the generation and manipulation of optics in the visible and near infrared (IR) range over the past decade. This is largely due to plasmonic enhancement, which has led to new technology in biosensing and molecule detection, solid-state lighting, and solar energy harvesting. The field of plasmonics uses quanta of plasma oscillations, plasmons, formed from the interaction between electromagnetic radiation and free electrons to enhance optical near field magnitudes. However, there is still a large region of the electromagnetic spectrum, covering the mid-infrared (MIR) and terahertz (THz) regions, ranging from 3 μm to 1 …

Interfacial Contact With Noble Metal - Noble Metal And Noble Metal - 2d Semiconductor Nanostructures Enhance Optical Activity, Ricardo Raphael Lopez Romo

Graduate Theses and Dissertations

Noble metal nanoparticles and two-dimensional (2D) transition metal dichalcogenide (TMD) crystals offer unique optical and electronic properties that include strong exciton binding, spin-orbital coupling, and localized surface plasmon resonance. Controlling these properties at high spatiotemporal resolution can support emerging optoelectronic coupling and enhanced optical features. Excitation dynamics of these optical properties on physicochemically bonded mono- and few-layer TMD crystals with metal nanocrystals and two overlapping spherical metal nanocrystals were examined by concurrently (i) DDA simulations and (ii) far-field optical transmission UV-vis spectroscopic measurements. Initially, a novel and scalable method to unsettle van der Waals bonds in bulk TMDs to prepare …

Integrated Chirped-Grating Spectrometer-On-A-Chip, Shima Nezhadbadeh

Optical Science and Engineering ETDs

In this dissertation we demonstrate a new structure based on waveguide coupling atop a silicon wafer using a chirped grating to provide the dispersion that leads to a high-resolution, compact, fully integrable and CMOS-compatible spectrometer. Light is both analyzed and detected in a single, completely monolithic component which enables realizing a high-resolution portable spectrometer with an extremely compact footprint. The structure is comprised of a SiO₂/Si₃N₄/SiO₂ waveguide on top of a silicon wafer. Grating regions are fabricated on the top cladding of the waveguide. The input light is incident on a chirped grating …

Near-Field Effects On Partially Coherent Light Scattered By An Aperture, Milo W. Hyde Iv, Michael J. Havrilla

Faculty Publications

We investigate how the near field affects partially coherent light scattered from an aperture in an opaque screen. Prior work on this subject has focused on the role of surface plasmons, and how they affect spatial coherence is well documented. Here, we consider other near-field effects that might impact spatial coherence. We do this by examining the statistics of the near-zone field scattered from an aperture in a perfect electric conductor plane—a structure that does not support surface plasmons. We derive the near-field statistics (in particular, cross-spectral density functions) by applying electromagnetic equivalence theorems and the Method of Moments. We …

Polarization Properties Of Airy And Ince-Gaussian Laser Beams, Sean Michael Nomoto

Graduate Theses and Dissertations

The description of polarization states of laser light as linear, circular polarization within the paraxial scalar wave approximation is adequate for most applications. However, this description falls short when considering laser light as an electromagnetic wave satisfying Maxwell's equations. An electric field with a constant unit vector for direction of the field and a space dependent complex scalar amplitude in the paraxial wave approximation does not satisfy Maxwell equations which, in general, requires all three Cartesian components of electric and magnetic fields associated for a nonzero laser beam to be nonzero.

Physical observation of passing a linearly polarized laser through …

Growth Of Indium Nitride Quantum Dots By Molecular Beam Epitaxy, Steven P. Minor

Graduate Theses and Dissertations

Over the last decade, the evolution of the global consciousness in response to decreasing environmental conditions from global warming and pollution has led to an outcry for finding new alternative/clean methods for harvesting energy and determining ways to minimize energy consumption. III-nitride materials are of interest for optoelectronic and electronic device applications such as high efficiency solar cells, solid state lighting (LEDs), and blue laser (Blu-ray Technology) applications. The wide range of direct band gaps covered by its alloys (0.7eV-6.2eV) best illustrates the versatility of III-nitride materials. This wide range has enabled applications extending from the ultraviolet to the near …

3d Plasmonic Design Approach For Efficient Transmissive Huygens Metasurfaces, Bryan M. Adomanis, D. Bruce Burckel, Michael A. Marciniak

Faculty Publications

In this paper we present a design concept for 3D plasmonic scatterers as high- efficiency transmissive metasurface (MS) building blocks. A genetic algorithm (GA) routine partitions the faces of the walls inside an open cavity into a M x N grid of voxels which can be either covered with metal or left bare, and optimizes the distribution of metal coverage needed to generate electric and magnetic modes of equal strength with a targeted phase delay (Φt) at the design wavelength. Even though the electric and magnetic modes can be more complicated than typical low order modes, with their spectral overlap …

Optical Response Analysis Of Thz Photoconductive Antenna Using Comsol Multiphysics, Jose Isaac Santos Batista

Electrical Engineering Undergraduate Honors Theses

A THz photoconductive antenna consists of antenna pads laid over a photoconductive substrate. These types of antennas are excited through the application of an optical pump (laser), which generates carriers inside the semiconductor. The acceleration and recombination of these carriers produce photocurrent that excites the antenna and generates THz pulse. This thesis focuses on analyzing the optical response of a photoconductive antenna, which consist of the interaction of the incident electric field of a laser pump with the radiating device. It develops the amplitude modulation process of a plane wave of light into a laser pump. It also takes into …

Designing Liquid Crystal For Optoacoustic Detection, Michael T. Dela Cruz

Theses and Dissertations

This research impacts the development of a cost-saving, on-chip device that can replace a wide range of costly, bulky sensors for commercial and defense applications. In particular, the goals of this work were to design and test a sensor that uses the optical properties of liquid crystal (LC) to detect acoustic waves. This began with developing a method to fine-tune the optical features of the liquid crystal. Statistical analysis of select experimental variables, or factors, lead to ideal settings of those variables when creating the sensor. A two-factor and three-factor experiment were separately conducted and analyzed as a preliminary demonstration …

A State-Of-The-Art Survey On Deep Learning Theory And Architectures, Md Zahangir Alom, Tarek M. Taha, Christopher Yakopcic, Stefan Westberg, Paheding Sidike, Mst Shamima Nasrin, Mahmudul Hasan, Brian C. Van Essen, Abdul A. S. Awwal, Vijayan K. Asari

Electrical and Computer Engineering Faculty Publications

In recent years, deep learning has garnered tremendous success in a variety of application domains. This new field of machine learning has been growing rapidly and has been applied to most traditional application domains, as well as some new areas that present more opportunities. Different methods have been proposed based on different categories of learning, including supervised, semi-supervised, and un-supervised learning. Experimental results show state-of-the-art performance using deep learning when compared to traditional machine learning approaches in the fields of image processing, computer vision, speech recognition, machine translation, art, medical imaging, medical information processing, robotics and control, bioinformatics, natural language …

Theoretical Analysis Of A Volume Holographic Lens Using Matlab, Sanjay Keshri, Kevin Murphy, Izabela Naydenova, Suzanne Martin

Conference Papers

Volume holographic lenses have great potential for different types of applications requiring light redirection and beam shaping such as solar light collection and LED light management. For lighting applications using LEDs, it is essential to make a highly efficient optical element to be placed in front of the LED in order to decrease energy losses. For that reason, a careful theoretical analysis of the properties and operation regime of the lens must be carried out at the design stage. The characteristics of focusing Holographic Optical Elements (HOE) depend on many factors including their thickness, spatial frequency, the angular range of …

Sensing Of Multiple Parameters With Whispering Gallery Mode Optical Fiber Micro-Resonators, Arun Kumar Mallik Dr, Vishnan Kavungal, Gerald Farrell, Yuliya Semenova

Conference Papers

Monitoring of multiple physical parameters, such as humidity, temperature, strain, concentrations of certain chemicals or gases in various environments is of great importance in many industrial applications both for minimizing adverse effects on human health as well as for maintaining production levels and quality of products. In this paper we demonstrate two different approaches to the design of multi-parametric sensors using coupled whispering gallery mode (WGM) optical fiber micro-resonators. In the first approach, a small array of micro-resonators is coupled to a single fiber taper, while in the second approach each of the micro-resonators within an array is coupled to …

Fundamental Properties Of Metallic Nanolasers, William Hayenga

Electronic Theses and Dissertations

The last two decades have witnessed tremendous advancements in the area of nanophotonics and plasmonics, which has helped propel the development of integrated photonic sources. Of central importance to such circuits is compact, scalable, low threshold, and efficient coherent sources that can be driven at high modulation frequencies. In this regard, metallic nanolasers offer a unique platform. Their introduction has enabled confinement of light at a subwavelength scale and the ultra-small size of the modes afforded by these structures allows for cavity enhancing effects that can help facilitate thresholdless lasing and large direct modulation bandwidths. In this report, I present …

Processing Of Advanced Infrared Materials, Daniel Mcgill

Electronic Theses and Dissertations

Infrared transparent glassy and crystalline materials often have unique and complex processing requirements but are an important class of materials for such applications as optical windows, lenses, waveplates, polarizers and beam splitters. This thesis investigates two specific materials, one amorphous and one crystalline, that are candidates for use in the short and midwave-infrared and mid and longwave infrared, respectively. It is demonstrated that an innovative uniaxial sintering process, which uses a sacrificial pressure-transmitting medium, can be used to fully densify a 70TeO2-20WO3-10La2O3 (TWL) glass powder. The characteristics of the sintered TWL glass is compared to that of a parent glass …

Active Recall Networks For Multiperspectivity Learning Through Shared Latent Space Optimization, Theus Aspiras, Ruixu Liu, Vijayan K. Asari

Electrical and Computer Engineering Faculty Publications

Given that there are numerous amounts of unlabeled data available for usage in training neural networks, it is desirable to implement a neural network architecture and training paradigm to maximize the ability of the latent space representation. Through multiple perspectives of the latent space using adversarial learning and autoencoding, data requirements can be reduced, which improves learning ability across domains. The entire goal of the proposed work is not to train exhaustively, but to train with multiperspectivity. We propose a new neural network architecture called Active Recall Network (ARN) for learning with less labels by optimizing the latent space. This …

Deep Temporal Convolutional Networks For Short-Term Traffic Flow Forecasting, Wentian Zhao, Yanyun Gao, Tingxiang Ji, Xili Wan, Feng Ye, Guangwei Bai

Electrical and Computer Engineering Faculty Publications

To reduce the increasingly congestion in cities, it is essential for intelligent transportation system (ITS) to accurately forecast the short-term traffic flow to identify the potential congestion sites. In recent years, the emerging deep learning method has been introduced to design traffic flow predictors, such as recurrent neural network (RNN) and long short-term memory (LSTM), which has demonstrated its promising results. In this paper, different from existing work, we study the temporal convolutional network (TCN) and propose a deep learning framework based on TCN model for short-term city-wide traffic forecast to accurately capture the temporal and spatial evolution of traffic …

High Performance Liquid Crystal Devices For Augmented Reality And Virtual Reality, Md Javed Rouf Talukder

Electronic Theses and Dissertations

See-through augmented reality and virtual reality displays are emerging due to their widespread applications in education, engineering design, medical, retail, transportation, automotive, aerospace, gaming, and entertainment. For augmented reality and virtual reality displays, high-resolution density, high luminance, fast response time and high ambient contrast ratio are critically needed. High-resolution density helps eliminate the screen-door effect, high luminance and fast response time enable low duty ratio operation, which plays a key role for suppressing image blurs. A dimmer placed in front of AR display helps to control the incident background light, which in turn improves the image contrast. In this dissertation, …

Imaging Through Glass-Air Anderson Localizing Optical Fiber, Jian Zhao

Electronic Theses and Dissertations

The fiber-optic imaging system enables imaging deeply into hollow tissue tracts or organs of biological objects in a minimally invasive way, which are inaccessible to conventional microscopy. It is the key technology to visualize biological objects in biomedical research and clinical applications. The fiber-optic imaging system should be able to deliver a high-quality image to resolve the details of cell morphology in vivo and in real time with a miniaturized imaging unit. It also has to be insensitive to environmental perturbations, such as mechanical bending or temperature variations. Besides, both coherent and incoherent light sources should be compatible with the …

Novel Solid State Lasers Based On Volume Bragg Gratings, Evan Hale

Electronic Theses and Dissertations

Since their invention in 1960, lasers have revolutionized modern technology, and tremendous amounts of innovation and development has gone into advancing their properties and efficiencies. This dissertation reports on further innovations by presenting novel solid state laser systems based on the volume Bragg gratings (VBGs) and the newly developed holographic phase mask (HPMs) for brightness enhancement, dual wavelength operation, and mode conversion. First, a new optical element was created by pairing the HPM with two surface gratings creating an achromatic holographic phase mask. This new optical device successfully performed transverse mode conversion of multiple narrow line laser sources operating from …

High-Dynamic-Range Foveated Near-Eye Display System, Guanjun Tan

Electronic Theses and Dissertations

Wearable near-eye display has found widespread applications in education, gaming, entertainment, engineering, military training, and healthcare, just to name a few. However, the visual experience provided by current near-eye displays still falls short to what we can perceive in the real world. Three major challenges remain to be overcome: 1) limited dynamic range in display brightness and contrast, 2) inadequate angular resolution, and 3) vergence-accommodation conflict (VAC) issue. This dissertation is devoted to addressing these three critical issues from both display panel development and optical system design viewpoints. A high-dynamic-range (HDR) display requires both high peak brightness and excellent dark …

Recurrent Residual U-Net For Medical Image Segmentation, Md Zahangir Alom, Christopher Yakopcic, Mahmudul Hasan, Tarek M. Taha, Vijayan K. Asari

Electrical and Computer Engineering Faculty Publications

Deep learning (DL)-based semantic segmentation methods have been providing state-of-the-art performance in the past few years. More specifically, these techniques have been successfully applied in medical image classification, segmentation, and detection tasks. One DL technique, U-Net, has become one of the most popular for these applications. We propose a recurrent U-Net model and a recurrent residual U-Net model, which are named RU-Net and R2U-Net, respectively. The proposed models utilize the power of U-Net, residual networks, and recurrent convolutional neural networks. There are several advantages to using these proposed architectures for segmentation tasks. First, a residual unit helps when training deep …

A Survey Of Techniques For Mobile Service Encrypted Traffic Classification Using Deep Learning, Pan Wang, Xuejiao Chen, Feng Ye, Zhixin Sun

Electrical and Computer Engineering Faculty Publications

The rapid adoption of mobile devices has dramatically changed the access to various net- working services and led to the explosion of mobile service traffic. Mobile service traffic classification has been a crucial task that attracts strong interest in mobile network management and security as well as machine learning communities for past decades. However, with more and more adoptions of encryption over mobile services, it brings a lot of challenges about mobile traffic classification. Although classical machine learning approaches can solve many issues that port and payload-based methods cannot solve, it still has some limitations, such as time-consuming, costly handcrafted …