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Albert Y. Zomaya

Researcher at University of Sydney

Publications -  1020
Citations -  30827

Albert Y. Zomaya is an academic researcher from University of Sydney. The author has contributed to research in topics: Cloud computing & Scheduling (computing). The author has an hindex of 75, co-authored 946 publications receiving 24637 citations. Previous affiliations of Albert Y. Zomaya include University of Alabama & University of Sheffield.

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Adaptive Model-Based Control using Neural Networks

TL;DR: In this article, a method for implementing a neural network model of nonlinear process dynamics for adaptive control was proposed and evaluated using two simulated realistic processes; level control of a conical tank and multivariable control of an industrial evaporator.
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GriDB: Scaling Blockchain Database via Sharding and Off-Chain Cross-Shard Mechanism

TL;DR: GriDB as discussed by the authors is a scalable blockchain database by designing an off-chain cross-shard mechanism for efficient crossshard database services, where the untrusted delegates cooperate to generate succinct proof for cross-share data exchanges, while the consensus is only responsible for low-cost proof verification.
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SInC: Semantic approach and enhancement for relational data compression

TL;DR: In this paper , a purely semantic approach, which losslessly compresses relational data in the first place and also enhances data file compression to further reduce the storage, is presented, and the original data can be entirely retrieved with the informative patterns induced by SInC .
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The implementation of novel idea of translation matrix to maintain QoS for a roaming user between heterogeneous 4G wireless networks

TL;DR: A novel mechanism for achieving service continuity through a Translation Matrix, which maps QoS parameters between different access networks, based on modeling the behavior of multiple classes of 4G traffic passing through different kinds of wireless IP domains implemented with different queuing and scheduling combinations.

A Bayesian analysis on historical clinical data concerning treatment change for HIV/AIDS patients

TL;DR: It is suggested that in a resource-constrained situation, an abridged historical viral load and CD4 archive can provide comparable prognostic support to a fully-populated archive with significantly reduced storage costs.