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In particular, knowledge sharing is important and strategies that support the translation of knowledge in networks have been categorised as having push, pull and exchange components [ 15].
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Internet factories include the use of libraries that capture years of experience and knowledge in network and systems engineering.
Some reverse engineering approaches, like ddepn[ 6] or CellNOptR[ 18], ideally join perturbed time course input data and literature prior knowledge in network reconstruction, while preserving the simplicity of Boolean logic at the same time.
Finally, on the basis of the empirical verification, we will consider the development of certain general principles for control in order to achieve greater efficiency in the management of knowledge in these networks.
A semantic network needs to be activated before meaningful connections between the prior knowledge in that network and the new information in the content and context can be made [ 13].
Data structures attached to graph elements (nodes, ports and edges) model local and global knowledge in the network, rewrite rules express elementary and local transformations, and strategies control the global evolution of the network.
In addition, the algorithm removes the training samples which are similar to the stored knowledge in the network.
With the introduction of theoretical knowledge in the network structure, the hybrid model results demonstrated a better prediction efficiency and reduced training time.
Each agent maintains two estimates of the system state: the first reflecting the common knowledge in the network, and the second additionally including all local sensor information.
The proposed method can efficiently utilize prior knowledge in the network inference while remaining robust to false positive edges in the knowledge.
Although connections with peers enable physicians a faster sharing of known knowledge [ 57], links with many peers significantly impacts an individual's opportunity to share or create knowledge in a network (e.g. PCN).
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