Zobrazeno 1 - 10
of 22
pro vyhledávání: '"Hazeline U. Asuncion"'
Publikováno v:
Informatics, Vol 5, Iss 2, p 18 (2018)
Agent-Based Models (ABMs) assist with studying emergent collective behavior of individual entities in social, biological, economic, network, and physical systems. Data provenance can support ABM by explaining individual agent behavior. However, there
Externí odkaz:
https://doaj.org/article/4589bbdce470439a919d91bfe719d655
Publikováno v:
eScience
Multi-agent simulations are useful for exploring collective patterns of individual behavior in social, biological, economic, network, and physical systems. However, there is no provenance support for multi-agent models (MAMs) in a distributed setting
Publikováno v:
ICDCS
Despite various cloud technologies that have parallelized and scaled up big data analysis, they target data mostly in texts which are easy to partition and thus easy to map over a cluster system. Therefore, their parallelization do not necessarily co
Autor:
Hazeline U. Asuncion, Destiny Boyer, Michael Stiber, Delmar B. Davis, Fumitaka Kawasaki, Jewel Yun-Hsuan Lee
Publikováno v:
IJCNN
Availability of affordable hardware that in effect enables desktop supercomputing has enabled more ambitious neural simulations driven by more complex software. However, this opportunity comes with costs, in terms of long learning curves to take adva
Publikováno v:
ICSA
Existing software product line approaches often develop and evolve product line features, architecture, and source code independently, which makes it difficult to manage the relationship and conformance between these artifacts. This paper presents a
Autor:
Hazeline U. Asuncion
Publikováno v:
Future Generation Computer Systems. 29:2169-2181
One of the most important tasks in eScience is capturing the provenance of data. While scientists frequently use off-the-shelf analysis tools to process and manipulate data, current provenance techniques such as those based on scientific workflows ar
Publikováno v:
Journal of the Association for Information Systems. 11:730-755
Autor:
Karen Potts, Delmar B. Davis, Nathan Duncan, Qi Zhang, Morteza Chini, Jonathan Mason, Hazeline U. Asuncion
Publikováno v:
e-Science
Researchers working in the North Creek Wetlands are faced with the task of gathering and managing large amounts of data. This interdisciplinary group of researchers also require data provenance to ensure the integrity of their collected data. Current
A substantial number of enterprises and independent software vendors are adopting a strategy in which software-intensive systems are developed with an open architecture (OA) that may contain open source software (OSS) components or components with op
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::475511ee867e8aadffefd13a7d471be1
https://doi.org/10.4018/978-1-4666-7230-7.ch001
https://doi.org/10.4018/978-1-4666-7230-7.ch001
Autor:
Kriti Gupta, Qi Zhang, Delmar B. Davis, Alex W.K. Wong, Hazeline U. Asuncion, Ailifan Aierken
Publikováno v:
eScience Workshops
When data are retrieved from a file storage system or the Internet, is there information about their provenance (i.e., their origin or history)? It is possible that data could have been copied from another source and then transformed. Often, provenan