Examples of using Distributed data in English and their translations into Thai
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Ecclesiastic
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Ecclesiastic
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Computer
Distributed data collection section 5.4.
Finally, one could argue that Peer-to-Patent is an example of distributed data collection.
Distributed data collection section 5.4.
Finally, one could argue that Peer-to-Patent is an example of distributed data collection.
Table 5.3: Examples of distributed data collection projects in social research.
PhotoCity solves the data quality and sampling problems in distributed data collection.
As eBird demonstrates, distributed data collection can be used for scientific research.
In fact, much of quantitative social science already relies on distributed data collection using paid staff.
Distributed data is stored in more than one set on site and across sites to help prevent data loss.
In addition to creating human computation and open calls, researchers can also create a distributed data collection project.
Distributed data collection is possible, and in the future it will likely involve technology and passive participation.
In addition to creating human computation and open call projects, researchers can also create distributed data collection projects.
In distributed data collection projects, researchers enable participants to contribute new measurements of the world.
In fact, much of quantitative social science already relies on distributed data collection in the form of surveys administered by employees.
Distributed data collection is possible, and in the future will likely involve technology and passive participation.
Overall, the PhotoCity project shows that sampling and data quality are not insurmountable problems in distributed data collection.
And find ways to make sure the distributed data processing is at least as efficient as centralized data processing.
And related projects, indicate that challenges related to sampling and data quality are concerns for distributed data collection projects.
Further, it shows that distributed data collection projects are not limited to tasks that people are already doing anyway, such as watching birds.
The ZooKeeper framework was originally built at“ Yahoo!” for accessing their applications in an easy and robust manner. Later, Apache ZooKeeper became a standard for organized service used by Hadoop, HBase, and other distributed frameworks. For example, Apache HBase uses ZooKeeper to track the status of distributed data. This tutorial explains the basics of ZooKeeper, how to install and deploy a ZooKeeper cluster in a distributed environment, and finally concludes with a few examples using Java programming and sample applications.
In fact, for certain research questions, distributed data collection is better than anything that would realistically be possible with paid data collectors.
Many organizations leverage the power of our distributed data centers to maximize critical benefits, such as minimal latency and robust geo-redundancy. However, for organizations with stringent control requirements, data regions for G Suite lets you choose where certain covered data should be stored at rest-either in the US, across Europe, or distributed globally.
As the examples below-from ornithology and computer science-show, distributed data collection enables researchers to collect data more frequently and in more places than were possible previously.
Many organizations leverage the power of our distributed data centers to maximize critical benefits, such as minimal latency and robust geo-redundancy. However, for organizations with stringent control requirements, data regions for G Suite lets you choose where certain covered data should be stored at rest-either in the US, across Europe, or distributed globally.
As the examples below-from ornithology and computer science-show distributed data collection enables researchers to collect data more frequently and in more places than were possible previously.
Going forward, I suspect that many distributed data collection projects will begin to make use of capabilities of mobile phones that are already carried by billions of people around the world.
Many organizations leverage the power of our distributed data centers to maximize critical benefits, such as minimal latency and robust geo-redundancy.
In fact, for certain research questions, distributed data collection is better than anything that would realistically be possible with paid data collectors.
Logical Replication- A publish/subscribe framework for distributing data.
Though based on the same concept of distributing data across a network of nodes, DLT and blockchain differ in the level of decentralisation.