Open Access. Powered by Scholars. Published by Universities.®
- Keyword
-
- Machine learning (2)
- Optics (2)
- 97 (1)
- Artificial intelligence (1)
- Block matching (1)
-
- Convolutional neural networks (1)
- Deep recurrent learning (1)
- Editorial (1)
- Fault identification (1)
- Finite element (1)
- GPU (1)
- Hospitality (1)
- ITK (1)
- Image guided neurosurgery (1)
- Intraoperative MRI (1)
- LINAC (1)
- Mathematics and computing (1)
- Maxwell equations (1)
- Non rigid registration (1)
- Particle accelerator (1)
- Pulse propagation (1)
- Qubits (1)
- Superconducting radio-frequency cavities (1)
- Time series classification (1)
- Unitary algorithms (1)
Articles 1 - 5 of 5
Full-Text Articles in Physics
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
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 …
Artificial Intelligence And Machine Learning In Optical Information Processing: Introduction To The Feature Issue, Khan Iftekharuddin, Chrysanthe Preza, Abdul Ahad S. Awwal, Michael E. Zelinski
Artificial Intelligence And Machine Learning In Optical Information Processing: Introduction To The Feature Issue, Khan Iftekharuddin, Chrysanthe Preza, Abdul Ahad S. Awwal, Michael E. Zelinski
Electrical & Computer Engineering Faculty Publications
This special feature issue covers the intersection of topical areas in artificial intelligence (AI)/machine learning (ML) and optics. The papers broadly span the current state-of-the-art advances in areas including image recognition, signal and image processing, machine inspection/vision and automotive as well as areas of traditional optical sensing, interferometry and imaging.
Deep Learning Based Superconducting Radio-Frequency Cavity Fault Classification At Jefferson Laboratory, Lasitha Vidyaratne, Adam Carpenter, Tom Powers, Chris Tennant, Khan M. Iftekharuddin, Md. Monibor Rahman, Anna S. Shabalina
Deep Learning Based Superconducting Radio-Frequency Cavity Fault Classification At Jefferson Laboratory, Lasitha Vidyaratne, Adam Carpenter, Tom Powers, Chris Tennant, Khan M. Iftekharuddin, Md. Monibor Rahman, Anna S. Shabalina
Electrical & Computer Engineering Faculty Publications
This work investigates the efficacy of deep learning (DL) for classifying C100 superconducting radio-frequency (SRF) cavity faults in the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab. CEBAF is a large, high-power continuous wave recirculating linac that utilizes 418 SRF cavities to accelerate electrons up to 12 GeV. Recent upgrades to CEBAF include installation of 11 new cryomodules (88 cavities) equipped with a low-level RF system that records RF time-series data from each cavity at the onset of an RF failure. Typically, subject matter experts (SME) analyze this data to determine the fault type and identify the cavity of …
Special Section Guest Editorial: Machine Learning In Optics, Jonathan Howe, Travis Axtell, Khan Iftekharuddin
Special Section Guest Editorial: Machine Learning In Optics, Jonathan Howe, Travis Axtell, Khan Iftekharuddin
Electrical & Computer Engineering Faculty Publications
This guest editorial summarizes the Special Section on Machine Learning in Optics.
An Itk Implementation Of A Physics-Based Non-Rigid Registration Method For Brain Deformation In Image Guided Neurosurgery, Yixun Liu, Andriy Kot, Fotis Drakopoulos, Chengjun Yao, Andriy Fedorov, Andinet Enquobahrie, Oliver Clatz, Nikos P. Chrisochoides
An Itk Implementation Of A Physics-Based Non-Rigid Registration Method For Brain Deformation In Image Guided Neurosurgery, Yixun Liu, Andriy Kot, Fotis Drakopoulos, Chengjun Yao, Andriy Fedorov, Andinet Enquobahrie, Oliver Clatz, Nikos P. Chrisochoides
Electrical & Computer Engineering Faculty Publications
As part of the ITK v4 project efforts, we have developed ITK filters for physics-based non-rigid registration (PBNRR), which satisfies the following requirements: account for tissue properties in the registration, improve accuracy compared to rigid registration, and reduce execution time using GPU and multi-core accelerators. The implementation has three main components: (1) Feature Point Selection, (2) Block Matching (mapped to both multi-core and GPU processors), and (3) a Robust Finite Element Solver. The use of multi-core and GPU accelerators in ITK v4 provides substantial performance improvements. For example, for the non-rigid registration of brain MRIs, the performance of the block …