Zobrazeno 1 - 10
of 81
pro vyhledávání: '"John K. Antonio"'
Publikováno v:
2022 IEEE/AIAA 41st Digital Avionics Systems Conference (DASC).
Publikováno v:
2021 IEEE/AIAA 40th Digital Avionics Systems Conference (DASC).
Machine learning (ML) is a powerful tool for solving stochastic optimization problems. The aerospace and defense sectors have a number of stochastic optimization problems that would benefit from the application of ML; however, people often have diffi
Publikováno v:
2020 AIAA/IEEE 39th Digital Avionics Systems Conference (DASC).
The DoD is increasingly employing agile methods in efforts to rapidly produce software. However, the specific domain of agile methodologies as applied to the sustainment of embedded systems remains in need of further research. One initial area examin
Autor:
John K. Antonio
Publikováno v:
IPDPS Workshops
Publikováno v:
2016 ASEE Annual Conference & Exposition Proceedings.
Publikováno v:
IEEE Transactions on Instrumentation and Measurement. 60:3767-3774
Some applications require wireless transmission of information to and from devices located inside metal enclosures, e.g., a closed shipping container in transit. However, traditional radio frequency (RF) communication schemes are not capable of trans
Publikováno v:
International Journal of Computational Science and Engineering. 14:105
Techniques for predicting the efficiency of multi-core processing associated with a set of tasks with varied CPU and main memory requirements are introduced. Prediction of CPU and memory availability is important in the context of making process assi
Publikováno v:
Advanced Information Systems Engineering ISBN: 9783642387081
NPC
NPC
Using Graphics Processing Units (GPUs) to solve general purpose problems has received significant attention both in academia and industry. Harnessing the power of these devices however requires knowledge of the underlying architecture and the program
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3e542d10133b04eeed3bfe99fe3978e1
https://doi.org/10.1007/978-3-662-44917-2_65
https://doi.org/10.1007/978-3-662-44917-2_65
Publikováno v:
INFOCOM
In this paper, we derive a time-complexity bound for the gradient projection method for optimal routing in data networks. This result shows that the gradient projection algorithm of Goldstein-Levitin-Poljak type formulated by Bertsekas (1982), Bertse