Mapping of Ice Sheet Deep Layers and Fast Outlet Glaciers with Multi-Channel-High-Sensitivity Radar

This dissertation discusses the waveform design, the development of SAR and clutter reduction algorithms for MCRDS radars that are developed at CReSIS to map the ice-sheet bed, deep internal layers and fast-flowing outlet glaciers. It is verified with survey data that the sidelobe level of the designed tapered linear chirp waveform is lower than -60dB for reliable detection of deep ice layers close to the bed. The SAR processing is implemented in f-k domain with motion compensation. Very weak echoes from the deepest parts of Jakobshavn channel are detected for the first time using large synthetic aperture length. A beam-spaced clutter-reduction algorithm is developed to reduce the distributed across-track ice clutter encountered in sounding fast outlet glaciers by estimating the clutter power as a function of depth. On average this method is able to reduce ice clutter by 10dB over Hanning weighting with the MCRDS radar's multi-channel data

Birefringence of GaN/AlGaN optical waveguides

This is the published version. Copyright © 2003 American Institute of PhysicsWe have experimentally studied the birefringence of wurtzite GaNgrown on a sapphire substrate. The measurements were done with single-mode GaN/AlGaN planar optical waveguides on c-plane grownheterostructure films. The refractive indices were found to be different for signal optical field perpendicular or parallel to the crystal c axis (n⊥≠n∥). More importantly, we found an approximately 10% change in index difference Δn=n∥−n⊥ with variation of the waveguide orientation in the a–b plane, and a 60° periodicity was clearly observed. This is attributed to the hexagonal structure of nitride materials

Skip-WaveNet: A Wavelet based Multi-scale Architecture to Trace Firn Layers in Radar Echograms

Echograms created from airborne radar sensors capture the profile of firn layers present on top of an ice sheet. Accurate tracking of these layers is essential to calculate the snow accumulation rates, which are required to investigate the contribution of polar ice cap melt to sea level rise. However, automatically processing the radar echograms to detect the underlying firn layers is a challenging problem. In our work, we develop wavelet-based multi-scale deep learning architectures for these radar echograms to improve firn layer detection. We show that wavelet based architectures improve the optimal dataset scale (ODS) and optimal image scale (OIS) F-scores by 3.99% and 3.7%, respectively, over the non-wavelet architecture. Further, our proposed Skip-WaveNet architecture generates new wavelets in each iteration, achieves higher generalizability as compared to state-of-the-art firn layer detection networks, and estimates layer depths with a mean absolute error of 3.31 pixels and 94.3% average precision. Such a network can be used by scientists to trace firn layers, calculate the annual snow accumulation rates, estimate the resulting surface mass balance of the ice sheet, and help project global sea level rise

GaN-based waveguide devices for long-wavelength optical communications

This is the published version. Copyright © 2003 American Institute of PhysicsRefractive indices of AlxGa1−xN with different Al concentrations have been measured in infrared wavelength regions. Single-mode ridged optical waveguidedevices using GaN/AlGaN heterostructures have been designed, fabricated, and characterized for operation in 1550 nm wavelength window. The feasibility of developing photonic integrated circuits based on III-nitride wide-band-gap semiconductors for fiber-optical communications has been discussed

Efficient Pyramid Channel Attention Network for Pathological Myopia Detection

Pathological myopia (PM) is the leading ocular disease for impaired vision and blindness worldwide. The key to detecting PM as early as possible is to detect informative features in global and local lesion regions, such as fundus tessellation, atrophy and maculopathy. However, applying classical convolutional neural networks (CNNs) to efficiently highlight global and local lesion context information in feature maps is quite challenging. To tackle this issue, we aim to fully leverage the potential of global and local lesion information with attention module design. Based on this, we propose an efficient pyramid channel attention (EPCA) module, which dynamically explores the relative importance of global and local lesion context information in feature maps. Then we combine the EPCA module with the backbone network to construct EPCA-Net for automatic PM detection based on fundus images. In addition, we construct a PM dataset termed PM-fundus by collecting fundus images of PM from publicly available datasets (e.g., the PALM dataset and ODIR dataset). The comprehensive experiments are conducted on three datasets, demonstrating that our EPCA-Net outperforms state-of-the-art methods in detecting PM. Furthermore, motivated by the recent pretraining-and-finetuning paradigm, we attempt to adapt pre-trained natural image models for PM detection by freezing them and treating the EPCA module and other attention modules as the adapters. The results show that our method with the pretraining-and-finetuning paradigm achieves competitive performance through comparisons to part of methods with traditional fine-tuning methods with fewer tunable parameters.Comment: 12 page

Subglacial topography and geothermal heat flux: potential interactions with drainage of the Greenland ice sheet

This is the published version, also available here: http://dx.doi.org/10.1029/2007GL030046.[1] Many of the outlet glaciers in Greenland overlie deep and narrow trenches cut into the bedrock. It is well known that pronounced topography intensifies the geothermal heat flux in deep valleys and attenuates this flux on mountains. Here we investigate the magnitude of this effect for two subglacial trenches in Greenland. Heat flux variations are estimated for idealized geometries using solutions for plane slopes derived by Lachenbruch (1968). It is found that for channels such as the one under Jakobshavn Isbræ, topographic effects may increase the local geothermal heat flux by as much as 100%