Tarun Luthra

Indian Institute of Technology Delhi

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S. Anandakrishnan

Pennsylvania State University

Richard B. Alley

Pennsylvania State University

Nicholas Holschuh

Lamont-Doherty Earth Observatory

Shivani Choudhary

Iowa State University

L. E. Peters

University of the West Indies

Andrew M. Smith

British Antarctic Survey

Himanshu Sundriyal

Jamia Millia Islamia

Mumtaz Ahmed

Jamia Millia Islamia

Sarfaraz Masood

Jamia Millia Islamia

Ashima Mittal

Indian Institute of Technology Delhi

Cooperative Institutions

Pennsylvania State University

Jamia Millia Islamia

Center for Remote Sensing and Integrated Systems

Indian Institute of Technology Delhi

University of California, Berkeley

Central Washington University

Lamont-Doherty Earth Observatory

Amherst College

Earth and Space Research

University of Washington

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Basal characteristics of the main sticky spot in the ice plain of Whillans Ice Stream

EGU General Assembly Conference Abstracts (2015)

Tarun Luthra S. Anandakrishnan Richard B. Alley Paul Winberry

Basal (medicine)

Ice wedge

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A Survey of Knowledge Graph Embedding and Their Applications.

arXiv (Cornell University) (2021)

Shivani Choudhary Tarun Luthra Ashima Mittal Rajat Singh

Knowledge Graph embedding provides a versatile technique for representing knowledge. These techniques can be used in a variety of applications such as completion of knowledge graph to predict missing information, recommender systems, question answering, query expansion, etc. The information embedded in Knowledge graph though being structured is challenging to consume in a real-world application. Knowledge graph embedding enables the real-world application to consume information to improve performance. Knowledge graph embedding is an active research area. Most of the embedding methods focus on structure-based information. Recent research has extended the boundary to include text-based information and image-based information in entity embedding. Efforts have been made to enhance the representation with context information. This paper introduces growth in the field of KG embedding from simple translation-based models to enrichment-based models. This paper includes the utility of the Knowledge graph in real-world applications.

Knowledge graph

Graph Embedding

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Feasibility study on the use of ICESat laser altimetry data for the study of Himalyan mountain glacier mass balance.

AGU Fall Meeting Abstracts (2007)

S. Anandakrishnan Tarun Luthra

Glacier mass balance

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Characteristics of the sticky spot of Kamb Ice Stream, West Antarctica

Journal of Geophysical Research Earth Surface (2017)

Tarun Luthra L. E. Peters S. Anandakrishnan Richard B. Alley Nicholas Holschuh

Abstract Amplitude analysis of reflection seismic data reveals the presence of highly variable bed conditions under the main sticky spot and adjacent regions of the Kamb Ice Stream (formerly ice stream C). The sticky spot, which is a zone of bed that imparts high basal resistance to ice flow, is situated on a local topographic high composed of consolidated sediments or sedimentary rock. Any meltwater draining from upglacier along the base of the ice is routed around the sticky spot. The ice over the sticky spot includes, in at least some places, a seismically detectable basal layer containing a low concentration of debris, which locally thickens to 40 m over a topographic low in the bed. The ice‐contact basal material ranges from dilated and highly porous to more‐compacted and stiff, and perhaps locally frozen. The softer material is preferentially in topographic lows, but there is not a one‐to‐one correspondence between basal character and basal topography. We speculate that the 40 m thick frozen‐on debris layer formed by glaciohydraulic supercooling of lake‐drainage events along a basal channel during the former, active phase of the ice stream. We also speculate that loss of lubricating water, perhaps from piracy upstream, contributed to the slowdown of the ice stream, with drag from the sticky spot playing an important role, and with the basal heterogeneity greatly increasing after the slowdown of the ice stream.

Meltwater

Ice wedge

Pancake ice

Fast ice

10.1002/2016jf004181

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Citations (7)

A Survey of Knowledge Graph Embedding and Their Applications

arXiv (Cornell University) (2021)

Shivani Choudhary Tarun Luthra Ashima Mittal Rajat Singh

Knowledge graph

Graph Embedding

10.48550/arxiv.2107.07842

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Citations (20)

Seismic Investigation of Sediments Beneath Antarctic Ice Streams

Tarun Luthra

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Characteristics of the sticky spot of Kamb Ice Stream, West Antarctica

EGUGA (2017)

Tarun Luthra L. E. Peters S. Anandakrishnan Richard B. Alley Nicholas Holschuh

Amplitude analysis of reflection seismic data reveals the presence of highly variable bed conditions under the main sticky spot and adjacent regions of the Kamb Ice Stream (KIS—formerly ice stream C). The sticky spot, which is a zone of bed that imparts high basal resistance to ice flow, is situated on a local topographic high composed of consolidated sediments or sedimentary rock. Any meltwater draining from upglacier along the base of the ice is routed around the sticky spot. The ice over the sticky spot includes, in at least some places, a seismically detectable basal layer containing a low concentration of debris, which locally thickens to 40 m over a topographic low in the bed. The ice-contact basal material ranges from dilated and highly porous to more-compacted and stiff, and perhaps locally frozen. The softer material is preferentially in topographic lows, but there is not a one-to-one correspondence between basal character and basal topography. We speculate that the 40-m-thick frozen-on debris layer formed by glaciohydraulic supercooling of lake-drainage events along a basal channel during the former, active phase of the ice stream. We also speculate that loss of lubricating water, perhaps from piracy upstream, contributed to the slowdown of the ice stream, with drag from the sticky spot playing an important role, and with the basal heterogeneity greatly increasing after the slowdown of the ice stream.

Meltwater

Ice wedge

Pancake ice

Fast ice

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Seismic imaging of former grounding lines beneath Whillans Ice Stream, West Antarctica

AGUFM (2013)

Tarun Luthra Richard B. Alley S. Anandakrishnan

Geophysical Imaging

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Basal characteristics of the main sticky spot on the ice plain of Whillans Ice Stream, Antarctica

Earth and Planetary Science Letters (2016)

Tarun Luthra S. Anandakrishnan J. Paul Winberry Richard B. Alley Nicholas Holschuh

Understanding the processes that affect streaming ice flow and the mass balance of glaciers and ice sheets requires sound knowledge of their subglacial environments. Previous studies have shown that an extensive deformable subglacial sediment layer favors fast ice-stream flow. However, areas of high basal drag, termed sticky spots, are of particular interest because they inhibit the fast flow of the overriding ice. The stick-slip behavior of Whillans Ice Stream (WIS) is perhaps the most conspicuous manifestation of a subglacial sticky spot. We present new ice-thickness and seismic-reflection measurements collected over the main sticky spot in the ice plain of WIS, allowing us to elucidate its role in the behavior of the ice stream. Ice-thickness and surface-elevation data show that the sticky spot occupies a subglacial topographic high. Water flow in response to the hydrological potential gradient will be routed around the sticky spot if effective pressures are similar on the sticky spot and elsewhere. The seismic experiment imaged a laterally continuous basal layer approximately 6 m thick, having compressional wave velocities of greater than 1800 m s−1 and density greater than 1800 kg m−3, indicative of a till layer that is stiffer than corresponding till beneath well-lubricated parts of the ice stream. This layer likely continues to deform under the higher shear stress of the sticky spot, and some water may be pumped up onto the sticky spot during motion events.

Ice divide

Pancake ice

10.1016/j.epsl.2016.01.035

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Citations (44)

Identification of diabetic retinopathy in eye images using transfer learning

Sarfaraz Masood Tarun Luthra Himanshu Sundriyal Mumtaz Ahmed

Convolutional Neural Networks have been performing exceptionally well for the recognition of worldly objects and there are various trained models available which can give you the class of an object if an image of the object is fed as their input. But, we can also retrain an already trained model for anotherset of classes of our interest and we have retrained such a model to check the severity of Diabetic Retinopathy in eye images (data has been provided by eyePacs as color fundus images) on the scale of 0-5. A convolutional neural network classifier engineered from Inception V3 network (trained for ImageNet) for 5-class severity classification performed best with an accuracy of 48.2%.

Transfer of learning

Contextual image classification

Fundus (uterus)

10.1109/ccaa.2017.8229977

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Citations (65)