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Alex Schultz

dblp:304/0091 · DBLP profile ↗
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2ranked-venue papers
0as first author
2since 2021 · last 2023
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Software engineering, systems software and programming languages · 1 · 1 since 2021Applied, interdisciplinary, general and emerging computing · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Cloud and datacenter computing · 100%
Network and information security
1 paper
Hardware security and side channels · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Cloud and datacenter computing › cloud security
confidential cloud computing
0.712023
An Extensible Orchestration and Protection Framework for Confidential Cloud Computing · OSDI 2023
Hardware security and side channels
trusted execution environments
0.212023
An Extensible Orchestration and Protection Framework for Confidential Cloud Computing · OSDI 2023
YearPublicationVenuePosition
2023 An Extensible Orchestration and Protection Framework for Confidential Cloud Computing
Adil Ahmad, Alex Schultz, Byoungyoung Lee, Pedro Fonseca 0001
OSDI2
2021 Olive Tree Water Stress Detection Using Daily Multispectral Imagery
abstract
Daily calibrated multispectral imagery (Planet Fusion) of an olive irrigation deficit trial was used to assess the degree and speed to which vegetation indices indicate water stress. We developed normalization techniques to increase sensitivity to differences across a grove. The normalized difference vegetation index (NDVI) was able to significantly detect differences between the control and deficit treatments for the Arbequina variety. For the Picual variety, the green red vegetation index (GRVI) was the best indicator. Though multispectral imagery is not as quick at indicating irrigation deficits as in-field sensor data, it is complementary in being able to capture the spatial variability of water stress.
James Brinkhoff, Alex Schultz, Luz Angelica Suarez, Andrew James Robson
IGARSS2