Sentence examples for datasets emerging from inspiring English sources

He develops human-AI frameworks to study, model, and (re design socio-technical systems, analyzing large-scale datasets emerging from human behavior, earth observation sensors, and socio-economic interactions.

Neil develops novel human-AI collaboration algorithms and tools to study, model, and (re-) design just socio-technical systems, analyzing large-scale datasets emerging from social processes, Earth remote sensing satellites, and socioeconomic interactions.

Recent years have witnessed an enormous growth of interest in efficient paradigms and techniques for representation, analysis, and processing of large-scale datasets emerging in various fields and applications, such as sensor and transportation networks, social networks and economic networks, and energy networks [1, 2].

This observed variance between datasets emerges either from actual differences in transcription factor binding (GABP binding in a more distributed manner), from variation in the preparation of samples (such as differences in antibody specificity or size selection during the preparation of the sequencing library) or a combination of such factors.

We will evaluate our integration approach when such datasets emerge in more detail.

When they saw our dataset emerge showing shallow wells were dangerously contaminated, even at levels beyond the WHO standard for safe wash water, they made a policy to not certify NGOs building shallow wells any more.

Due to the low statistical support for many relationships within Pelecaniformes and the waterbird clade, as well as enduring conflicts between datasets, an emerging consensus of recent studies is that additional data and revision are needed for both molecular and morphological datasets.

Large datasets are emerging in many fields of image processing including: electron microscopy, light microscopy, medical X-ray imaging, astronomy, etc. Novel computer-controlled instrumentation facilitates the collection of very large datasets containing thousands of individual digital images.

Massive datasets in emerging fields such as geosciences, biology, and networking do require parallel and distributed computations with high performance to solve real-world problems.

Here, we report our progress in the analyses of these datasets and emerging "comparative phylogenomics" insights into Oryza evolution at two different resolutions chromosomal and sequence levels.

Therefore, distributed computing platforms based on MapReduce paradigm, which uses thousands of commodity machines to process and analyze huge datasets, are emerging as the best solution for growing genomics data.