Application of this method to larger scale tasks is one of our future goals.
"In Reviving New Orleans, a Challenge of Many Tiers" (news article, Sept. 12) describes the large-scale task of rebuilding infrastructure, housing, businesses and services.
The basic idea is to recursively split a large-scale task in half, and then those halves are further split until the scale of subtasks is small enough.
Besides, we investigate two dimension reduction methods: Tensor Sketch approximation [9] and Mutual Information dimension selection [10] to compact FV-CNN which is rather high-dimensional and cannot be generalized to large-scale task.
Because the large-scale task cannot be completed within one I λ, we should decide on the type of VM to rent for each incomplete task in every auction.
In the final article, "Large-scale global optimization through consensus of opinions over complex networks" by Omid Askari-Sichani and Mahdi Jalili, the authors present a model based on consensus of opinions among agents interacting over a complex networked structure for a large-scale task optimization.
Chen et al. [29] make the difference between large-scale task coordination, where the platform proactively recommends tasks to the crowd in a coordinated way, and predictive crowd-tasking, where the recommendation of tasks is not solely based on current location.
To establish these teams, staff establishments need to be redesigned; numerous new posts will have to be created and their contents defined; current scopes of practice (roles and tasks) will have to be redefined and reassigned; and, large-scale task shifting/task sharing will have to take place.
To illustrate how methodological rigor in NA practice and reporting can be achieved, we detail the methods and procedure followed in a large-scale task-based NA conducted for non-native English speakers working at a national research institution in the USA.
At last, an efficient image retrieval system is designed and realized based on a cloud-based heterogeneous computing framework through Apache Spark and multiple GPUs to deal with large-scale tasks.
In spite of its advantageous flexibility and availability [6, 7], the software-based approaches fail to cope with large-scale tasks such as pattern recognition, learning, and intelligent cognition [8, 9], and also causes several orders of magnitude higher energy consumption than the human brain [10].
