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A maximum of 60 patients per general practitioner was invited to minimize workload for general practitioners.
Particular emphasis is being put on the use of routine data (e.g. data from patients' health records) in order to minimize workload for the participating hospitals and to reduce the burden which additional diagnostic procedures and clinical evaluations might impose upon the patients and their carers.
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In [35], Dong et al. proposed a randomized task assignment framework for computing tasks on participatory smartphones in a reliable fashion while minimizing workload at individual participatory devices.
The aims of the model include minimizing the fixed/variable cost of the machinery, maintenance and repair cost, inter-cell movement cost, maximizing the utilization of the machine, and minimizing workload variance of the different cells.
To strike the right balance among efficacy (avoiding persistent hyperglycemia), safety (avoiding hypoglycemia), and attainability (minimizing workload increase) different protocols have been developed.
The results also suggest advantages of considering the dissimilarities of leading and non-leading roles and their discrete demands during CPR, minimizing workload demands and role conflicts for both leader and non-leader team members.
Hence, the idea of the local search algorithm is to target a loop with maximum workload and attempt to minimize its workload.
We introduce the design and implementation of a novel Pareto-based scheduler that, given a user's MapReduce workload and budget range, detects map/reduce slot allocations that minimize the workload's makespan without overcharging the user.
The key contributions of our work are as follows: We introduce the design and implementation of a novel Pareto-based scheduler that, given a user's MapReduce workload and budget range, detects map/reduce slot allocations that minimize the workload's makespan without overcharging the user.
The second objective is to minimize the workload imbalances among cells.
Objective function of moves The objective of the partitioning problem is to minimize the workload of the system.
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