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With the model of tasks, the inputs and the according state can be send to the tasks and they can concurrently execute several substeps.
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The regularizer J ( w 1, …, w T ) forces the model of task 1 (w1) to be more similar to the model of task 2 (w2).
In this paper, we introduce a model of task scheduling for a cloud-computing data center to analyze energy-efficient task scheduling.
Our work has implications for a transferable, interdisciplinary model of task-based, situated learning which can be applied and adapted to different skill and knowledge sets.
A collection of 20 greedy heuristics, including 17 newly proposed ones, are implemented, analyzed, and systematically compared within a uniform model of task execution time.
The hierarchy defines the psychological ordering among the attributes required to solve a test problem, and thus serves as the cognitive model of task performance.
The AHM is a psychometric method for classifying examinees' test item responses into a set of structured attribute patterns associated with different components specified in a cognitive model of task performance.
This paper describes two experiments designed to investigate how a current model of task perseveration, the mood-as-input hypothesis, might be applied to activities relevant to compulsive checking.
The results of this study support the model of task-irrelevant learning put forth by Seitz and Watanabe [1].
To address this question we used adaptive biasing force (ABF) calculations [24] on a homology model of TASK-2 [20].
Our results imply that while the decision process itself is delayed during multiple task execution, its workings are unaffected by task interference, providing strong evidence in favor of a sequential model of task execution.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com