Open Access. Powered by Scholars. Published by Universities.®
- Institution
- Keyword
-
- Bilateral filter (1)
- Convolutional neural network (1)
- Dielectric materials (1)
- Diffusion (1)
- Electromagnetic pulse (1)
-
- Field theory (1)
- Fluxgate magnetometers (1)
- Fusion experiments (1)
- Hall probes (1)
- Hexagonal sampling (1)
- Holes (1)
- Image restoration (1)
- Instruments (1)
- Light fields (1)
- Liquid helium (1)
- Magnetic fields (1)
- Magnetic flux (1)
- Magnetoresistivity (1)
- Maxwell equations (1)
- Molecules (1)
- Nanofibers (1)
- Nonlocal means (1)
- Optical beams (1)
- Optical engineering (1)
- Optical properties (1)
- Optical waveguides (1)
- Particle accelerators (1)
- Peptides and proteins (1)
- Plasmas (1)
- Q factors (1)
Articles 1 - 18 of 18
Full-Text Articles in Physics
Evaluating Deep-Learning Models For Debris-Covered Glacier Mapping, Zhiyuan Xie, Vijayan K. Asari, Umesh K. Haritashya
Evaluating Deep-Learning Models For Debris-Covered Glacier Mapping, Zhiyuan Xie, Vijayan K. Asari, Umesh K. Haritashya
Electrical and Computer Engineering Faculty Publications
In recent decades, mountain glaciers have experienced the impact of climate change in the form of accelerated glacier retreat and other glacier-related hazards such as mass wasting and glacier lake outburst floods. Since there are wide-ranging societal consequences of glacier retreat and hazards, monitoring these glaciers as accurately and repeatedly as possible is important. However, the accurate glacier boundary, especially the debriscovered glacier (DCG) boundary, which is one of the primary inputs in many glacier analyses, remains a challenge even after many years of research using conventional remote sensing methods or machine-learning methods. The GlacierNet, a deep-learning-based approach, utilized the …
Single-Molecule Localization Microscopy Of 3d Orientation And Anisotropic Wobble Using A Polarized Vortex Point Spread Function, Tianben Ding, Matthew D. Lew
Single-Molecule Localization Microscopy Of 3d Orientation And Anisotropic Wobble Using A Polarized Vortex Point Spread Function, Tianben Ding, Matthew D. Lew
Electrical & Systems Engineering Publications and Presentations
Within condensed matter, single fluorophores are sensitive probes of their chemical environments, but it is difficult to use their limited photon budget to image precisely their positions, 3D orientations, and rotational diffusion simultaneously. We demonstrate the polarized vortex point spread function (PSF) for measuring these parameters, including characterizing the anisotropy of a molecule’s wobble, simultaneously from a single image. Even when imaging dim emitters (∼500 photons detected), the polarized vortex PSF can obtain 12 nm localization precision, 4°–8° orientation precision, and 26° wobble precision. We use the vortex PSF to measure the emission anisotropy of fluorescent beads, the wobble dynamics …
Resampling And Super-Resolution Of Hexagonally Sampled Images Using Deep Learning, Dylan Flaute, Russell C. Hardie, Hamed Elwarfalli
Resampling And Super-Resolution Of Hexagonally Sampled Images Using Deep Learning, Dylan Flaute, Russell C. Hardie, Hamed Elwarfalli
Electrical and Computer Engineering Faculty Publications
Super-resolution (SR) aims to increase the resolution of imagery. Applications include security, medical imaging, and object recognition. We propose a deep learning-based SR system that takes a hexagonally sampled low-resolution image as an input and generates a rectangularly sampled SR image as an output. For training and testing, we use a realistic observation model that includes optical degradation from diffraction and sensor degradation from detector integration. Our SR approach first uses non-uniform interpolation to partially upsample the observed hexagonal imagery and convert it to a rectangular grid. We then leverage a state-of-the-art convolutional neural network (CNN) architecture designed for SR …
A Unified Framework Of Deep Learning-Based Facial Expression Recognition System For Diversified Applications, Sanoar Hossain, Saiyed Umer, Vijayan K. Asari, Ranjeet Kumar Rout
A Unified Framework Of Deep Learning-Based Facial Expression Recognition System For Diversified Applications, Sanoar Hossain, Saiyed Umer, Vijayan K. Asari, Ranjeet Kumar Rout
Electrical and Computer Engineering Faculty Publications
This work proposes a facial expression recognition system for a diversified field of appli- cations. The purpose of the proposed system is to predict the type of expressions in a human face region. The implementation of the proposed method is fragmented into three components. In the first component, from the given input image, a tree-structured part model has been applied that predicts some landmark points on the input image to detect facial regions. The detected face region was normalized to its fixed size and then down-sampled to its varying sizes such that the advantages, due to the effect of multi-resolution …
Wavelength And Power Dependence On Multilevel Behavior Of Phase Change Materials, Gary A. Sevison, Joshua A. Burrow, Haiyun Guo, Andrew M. Sarangan, Joshua R. Hendrickson, Imad Agha
Wavelength And Power Dependence On Multilevel Behavior Of Phase Change Materials, Gary A. Sevison, Joshua A. Burrow, Haiyun Guo, Andrew M. Sarangan, Joshua R. Hendrickson, Imad Agha
Electro-Optics and Photonics Faculty Publications
We experimentally probe the multilevel response of GeTe, Ge2Sb2Te5 (GST), and 4% tungsten-doped GST (W-GST) phase change materials (PCMs) using two wavelengths of light: 1550 nm, which is useful for telecom-applications, and near-infrared 780 nm, which is a standard wavelength for many experiments in atomic and molecular physics. We find that the materials behave differently with the excitation at the different wavelengths and identify useful applications for each material and wavelength. We discuss thickness variation in the thin films used as well and comment on the interaction of the interface between the material and the substrate with regard to the …
Experimental Observation Of Topological Z2 Excitonpolaritons In Transition Metal Dichalcogenide Monolayers, Mengyao Li, Ivan Sinev, Fedor Benimetskiy, Tatyana Ivanova, Ekaterina Khestanova, Svetlana Kiriushechkina, Anton Vakulenko, Sriram Guddala, Maurice Skolnick, Vinod M. Menon, Dmitry Krizhanovskii, Andrea Alù, Anton Samusev, Alexander B. Khanikaev
Experimental Observation Of Topological Z2 Excitonpolaritons In Transition Metal Dichalcogenide Monolayers, Mengyao Li, Ivan Sinev, Fedor Benimetskiy, Tatyana Ivanova, Ekaterina Khestanova, Svetlana Kiriushechkina, Anton Vakulenko, Sriram Guddala, Maurice Skolnick, Vinod M. Menon, Dmitry Krizhanovskii, Andrea Alù, Anton Samusev, Alexander B. Khanikaev
Publications and Research
The rise of quantum science and technologies motivates photonics research to seek new platforms with strong light-matter interactions to facilitate quantum behaviors at moderate light intensities. Topological polaritons (TPs) offer an ideal platform in this context, with unique properties stemming from resilient topological states of light strongly coupled with matter. Here we explore polaritonic metasurfaces based on 2D transition metal dichalcogenides (TMDs) as a promising platform for topological polaritonics. We show that the strong coupling between topological photonic modes of the metasurface and excitons in TMDs yields a topological polaritonic Z2 phase. We experimentally confirm the emergence of one-way …
Optical Switching Performance Of Thermally Oxidized Vanadium Dioxide With An Integrated Thin Film Heater, Andrew M. Sarangan, Gamini Ariyawansa, Ilya Vitebskiy, Igor Anisimov
Optical Switching Performance Of Thermally Oxidized Vanadium Dioxide With An Integrated Thin Film Heater, Andrew M. Sarangan, Gamini Ariyawansa, Ilya Vitebskiy, Igor Anisimov
Electro-Optics and Photonics Faculty Publications
Optical switching performance of vanadium dioxide produced by thermal oxidation of vanadium is presented in this paper. A 100nm thick vanadium was oxidized under controlled conditions in a quartz tube furnace to produce approximately 200nm thick VO2. The substrate was appropriately coated on the front and back side to reduce reflection in the cold state, and an integrated thin film heater was fabricated to allow in-situ thermal cycling. Electrical measurements show a greater than three orders of magnitude change in resistivity during the phase transition. Optical measurements exhibit 70% transparency at 1500nm and about 15dB extinction across a wide spectral …
Guest Editorial: Edge Intelligence For Beyond 5g Networks, Yan Zhang, Zhiyong Feng, Hassnaa Moustafa, Feng Ye, Usman Javaid, Chunfen Cui
Guest Editorial: Edge Intelligence For Beyond 5g Networks, Yan Zhang, Zhiyong Feng, Hassnaa Moustafa, Feng Ye, Usman Javaid, Chunfen Cui
Electrical and Computer Engineering Faculty Publications
Beyond fifth-generation (B5G) networks, or so-called "6G", is the next-generation wireless communications systems that will radically change how Society evolves. Edge intelligence is emerging as a new concept and has extremely high potential in addressing the new challenges in B5G networks by providing mobile edge computing and edge caching capabilities together with Artificial Intelligence (AI) to the proximity of end users. In edge intelligence empowered B5G networks, edge resources are managed by AI systems for offering powerful computational processing and massive data acquisition locally at edge networks. AI helps to obtain efficient resource scheduling strategies in a complex environment with …
Twisted Spatiotemporal Optical Vortex Random Fields, Milo W. Hyde Iv
Twisted Spatiotemporal Optical Vortex Random Fields, Milo W. Hyde Iv
Faculty Publications
We present twisted spatiotemporal optical vortex (STOV) beams, which are partially coherent light sources that possess a coherent optical vortex and a random twist coupling their space and time dimensions. These beams have controllable partial coherence and transverse orbital angular momentum (OAM), which distinguishes them from the more common spatial vortex and twisted beams (known to carry longitudinal OAM) in the literature and should ultimately make them useful in applications such as optical communications and optical tweezing. We present the mathematical analysis of twisted STOV beams, deriving the mutual coherence function and linear and angular momentum densities. We simulate the …
Color-Compressive Bilateral Filter And Nonlocal Means For High-Dimensional Images, Christina Karam, Kenjiro Sugimoto, Keigo Hirakawa
Color-Compressive Bilateral Filter And Nonlocal Means For High-Dimensional Images, Christina Karam, Kenjiro Sugimoto, Keigo Hirakawa
Electrical and Computer Engineering Faculty Publications
We propose accelerated implementations of bilateral filter (BF) and nonlocal means (NLM) called color-compressive bilateral filter (CCBF) and color-compressive nonlocal means (CCNLM). CCBF and CCNLM are random filters, whose Monte-Carlo averaged output images are identical to the output images of conventional BF and NLM, respectively. However, CCBF and CCNLM are considerably faster because the spatial processing of multiple color channels are combined into a single random filtering process. This implies that the complexity of CCBF and CCNLM is less sensitive to color dimension (e.g., hyperspectral images) relatively to other BF and NLM methods. We experimentally verified that the execution time …
Deep Learning For Anisoplanatic Optical Turbulence Mitigation In Long-Range Imaging, Matthew A. Hoffmire, Russell C. Hardie, Michael A. Rucci, Richard Van Hook, Barry K. Karch
Deep Learning For Anisoplanatic Optical Turbulence Mitigation In Long-Range Imaging, Matthew A. Hoffmire, Russell C. Hardie, Michael A. Rucci, Richard Van Hook, Barry K. Karch
Electrical and Computer Engineering Faculty Publications
We present a deep learning approach for restoring images degraded by atmospheric optical turbulence. We consider the case of terrestrial imaging over long ranges with a wide field-of-view. This produces an anisoplanatic imaging scenario where turbulence warping and blurring vary spatially across the image. The proposed turbulence mitigation (TM) method assumes that a sequence of short-exposure images is acquired. A block matching (BM) registration algorithm is applied to the observed frames for dewarping, and the resulting images are averaged. A convolutional neural network (CNN) is then employed to perform spatially adaptive restoration. We refer to the proposed TM algorithm as …
Plasmon-Driven Nanowire Actuators For On-Chip Manipulation, Shuangyi Linghu, Zhaoqi Gu, Jinsheng Lu, Wei Fang, Zongyin Yang, Huakang Yu, Zhiyuan Li, Runlin Zhu, Jian Peng, Qiwen Zhan, Songlin Zhuang1, Min Gu, Fuxing Gu
Plasmon-Driven Nanowire Actuators For On-Chip Manipulation, Shuangyi Linghu, Zhaoqi Gu, Jinsheng Lu, Wei Fang, Zongyin Yang, Huakang Yu, Zhiyuan Li, Runlin Zhu, Jian Peng, Qiwen Zhan, Songlin Zhuang1, Min Gu, Fuxing Gu
Electro-Optics and Photonics Faculty Publications
Chemically synthesized metal nanowires are promising building blocks for next-generation photonic integrated circuits, but technological implementation in monolithic integration will be severely hampered by the lack of controllable and precise manipulation approaches, due to the strong adhesion of nanowires to substrates in non-liquid environments. Here, we demonstrate this obstacle can be removed by our proposed earthworm-like peristaltic crawling motion mechanism, based on the synergistic expansion, friction, and contraction in plasmon-driven metal nanowires in non-liquid environments. The evanescently excited sur- face plasmon greatly enhances the heating effect in metal nanowires, thereby generating surface acoustic waves to drive the nanowires crawling along …
On-Chip Silicon Photonic Controllable 2 × 2 Four-Mode Waveguide Switch, Cao Dung Truong, Duy Nguyen Thi Hang, Hengky Chandrahalim, Minh Tuan Trinh
On-Chip Silicon Photonic Controllable 2 × 2 Four-Mode Waveguide Switch, Cao Dung Truong, Duy Nguyen Thi Hang, Hengky Chandrahalim, Minh Tuan Trinh
Faculty Publications
Multimode optical switch is a key component of mode division multiplexing in modern high-speed optical signal processing. In this paper, we introduce for the first time a novel 2 × 2 multimode switch design and demonstrate in the proof-of-concept. The device composes of four Y-multijunctions and 2 × 2 multimode interference coupler using silicon-on-insulator material with four controllable phase shifters. The shifters operate using thermo-optic effects utilizing Ti heaters enabling simultaneous switching of the optical signal between the output ports on four quasi-transverse electric modes with the electric power consumption is in order of 22.5 mW and the switching time …
Tunable Optical Filter Using Phase Change Materials For Smart Ir Night Vision Applications, Remona Heenkenda, Keigo Hirakawa, Andrew Sarangan
Tunable Optical Filter Using Phase Change Materials For Smart Ir Night Vision Applications, Remona Heenkenda, Keigo Hirakawa, Andrew Sarangan
Electro-Optics and Photonics Faculty Publications
In this paper we present a tunable filter using Ge2Sb2Se4Te1 (GSST) phase change material. The design principle of the filter is based on a metal-insulator-metal (MIM) cavity operating in the reflection mode. This is intended for night vision applications that utilize 850nm as the illumination source. The filter allows us to selectively reject the 850nm band in one state. This is illustrated through several daytime and nighttime imaging applications.
Magnetic Field Sensors For Detection Of Trapped Flux In Superconducting Radio Frequency Cavities, Ishwari Prasad Parajuli, Gianluigi Ciovati, Jean R. Delayen
Magnetic Field Sensors For Detection Of Trapped Flux In Superconducting Radio Frequency Cavities, Ishwari Prasad Parajuli, Gianluigi Ciovati, Jean R. Delayen
Physics Faculty Publications
Superconducting radio frequency (SRF) cavities are fundamental building blocks of modern particle accelerators. They operate at liquid helium temperatures (2–4 K) to achieve very high quality factors (1010–1011). Trapping of magnetic flux within the superconductor is a significant contribution to the residual RF losses, which limit the achievable quality factor. Suitable diagnostic tools are in high demand to understand the mechanisms of flux trapping in technical superconductors, and the fundamental components of such diagnostic tools are magnetic field sensors. We have studied the performance of commercially available Hall probes, anisotropic magnetoresistive sensors, and flux-gate magnetometers with …
Ieee Access Special Section Editorial: Trends And Advances In Bio-Inspired Image-Based Deep Learning Methodologies And Applications, Peter Peer, Carlos M. Travieso-Gonzalez, Vijayan K. Asari, Malay Kishore Dutta
Ieee Access Special Section Editorial: Trends And Advances In Bio-Inspired Image-Based Deep Learning Methodologies And Applications, Peter Peer, Carlos M. Travieso-Gonzalez, Vijayan K. Asari, Malay Kishore Dutta
Electrical and Computer Engineering Faculty Publications
Many of the technological advances we enjoy today have been inspired by biological systems due to their ease of operation and outstanding efficiency. Designing technological solutions based on biological inspiration has become a cornerstone of research in a variety of areas ranging from control theory and optimization to computer vision, machine learning, and artificial intelligence. Especially in the latter few areas, biologically relevant solutions are becoming increasingly important as we look for new ways to make artificial systems more efficient, intelligent, and overall effective.
Dales Objects: A Large Scale Benchmark Dataset For Instance Segmentation In Aerial Lidar, Nina M. Singer, Vijayan K. Asari
Dales Objects: A Large Scale Benchmark Dataset For Instance Segmentation In Aerial Lidar, Nina M. Singer, Vijayan K. Asari
Electrical and Computer Engineering Faculty Publications
We present DALES Objects, a large-scale instance segmentation benchmark dataset for aerial lidar. DALES Objects contains close to half a billion hand-labeled points, including semantic and instance segmentation labels. DALES Objects is an extension of the DALES (Varney et al., 2020) dataset, adding additional intensity and instance segmentation annotation. This paper provides an overview of the data collection, preprocessing, hand-labeling strategy, and final data format. We propose relevant evaluation metrics and provide insights into potential challenges when evaluating this benchmark dataset. Finally, we provide information about how researchers can access the dataset for their use at go.udayton.edu/dales3d.
Reflection And Transmission Of Electromagnetic Pulses At A Planar Dielectric Interface: Theory And Quantum Lattice Simulations, Abhay K. Ram, George Vahala, Linda Vahala, Min Soe
Reflection And Transmission Of Electromagnetic Pulses At A Planar Dielectric Interface: Theory And Quantum Lattice Simulations, Abhay K. Ram, George Vahala, Linda Vahala, Min Soe
Electrical & Computer Engineering Faculty Publications
There is considerable interest in the application of quantum information science to advance computations in plasma physics. A particular point of curiosity is whether it is possible to take advantage of quantum computers to speed up numerical simulations relative to conventional computers. Many of the topics in fusion plasma physics are classical in nature. In order to implement them on quantum computers, it will require couching a classical problem in the language of quantum mechanics. Electromagnetic waves are routinely used in fusion experiments to heat a plasma or to generate currents in the plasma. The propagation of electromagnetic waves is …