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Now showing items 11-20 of 30
A data analytic algorithm for managing, querying, and processing uncertain big data in cloud environments
(MDPI, 2015-12)
Big data are everywhere as high volumes of varieties of valuable precise and uncertain data can be easily collected or generated at high velocity in various real-life applications. Embedded in these big data are rich sets ...
Edge-based mining of frequent subgraphs from graph streams
(Elsevier, 2015)
In the current era of Big data, high volumes of valuable data can be generated at a high velocity from high-varieties of data sources in various real-life applications ranging from sensor networks to social networks, from ...
Approximation to expected support of frequent itemsets in mining probabilistic sets of uncertain data
(Elsevier, 2015)
Knowledge discovery and data mining generally discovers implicit, previously unknown, and useful knowledge from data. As one of the popular knowledge discovery and data mining tasks, frequent itemset mining, in particular, ...
Frequent subgraph mining from streams of linked graph structured data
(CEUR Workshop Proceedings, 2015)
Nowadays, high volumes of high-value data (e.g., semantic web data) can be generated and published at a high velocity. A collection of these data can be viewed as a big, interlinked, dynamic graph structure of linked ...
Boundary detection of pigs in pens based on adaptive thresholding using an integral image and adaptive partitioning
(CMU Press, 2017-04)
Boundary detection of pigs is important to pig weight estimation, pig feeding behavior analysis, and thermal comfort control. This research proposes a boundary detection method for pigs in a feeder zone with a high-density ...
Game data mining: clustering and visualization of online game data in cyber-physical worlds
(Elsevier, 2017)
Since its debut in May 2016, Overwatch has quickly become a popular team-based online video game. Despite the popularity of Overwatch, many new players---who join the game unsure how to compete with the game’s veterans---feel ...
A two-dimensional sparse matrix profile DenseNet for COVID-19 diagnosis using chest CT images
(IEEE, 2020)
COVID-19 is a newly identified disease, which is very contagious and has been rapidly spreading across different countries around the world, calling for rapid and accurate diagnosis tools. Chest CT imaging has been widely ...
Operon-based approach for the inference of rRNA and tRNA evolutionary histories in bacteria
(Springer Nature, 2020)
In bacterial genomes, rRNA and tRNA genes are often organized into operons, i.e., segments of closely located genes that share a single promoter and are transcribed as a single unit. Analyzing how these genes and operons ...
Predictive analytics on open big data for supporting smart transportation services
(Elsevier, 2020)
In the current era of big data, huge quantities of valuable data, which may be of different levels of veracity, are being generated at a rapid rate. Embedded into these big data are implicit, previously unknown and potentially ...
Operon-based approach for the inference of rRNA and tRNA evolutionary histories in bacteria
(2020-04-16)
Abstract
Background
In bacterial genomes, rRNA and tRNA genes are often organized into operons, i.e. segments of closely located genes that share a single promoter and are transcribed as a single unit. Analyzing how these ...