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The REP-EQUITY toolkit guides representative and equitable inclusion in research. The toolkit was developed through a methodological systematic review and synthesis and finalized in a consensus workshop with 24 participants. The REP-EQUITY toolkit describes seven steps for investigators to consider in ...
Favorable social relations are beneficial for company to establish positive organization image, thus reinforce the knowledge acquisition process. Following Liao and Welsch’s research, this paper concentrates on trust in relational dimension among memberships and consequently argues H5: The higher the ...
This ICCV paper is the Open Access version, provided by the Computer Vision Foundation. Except for this watermark, it is identical to the accepted version; the final published version of the proceedings is available on IEEE Xplore. Learning to Upsample by Learning to Sample Wenze Liu Hao Lu*...
This can lead to benefits such as shorter study duration and lower financial costs, which are key considerations when investigating treatments for uncommon disorders or new agents in proof-of- concept studies, and this could make a project proposal being considered for funding more attractive when ...
The paper is structured as follows. In Section “Model and definition” we present the linear model that relates a trait with a genotype matrix, then narrow-sense heritability is defined together with some discussion regarding the fixed-effect vs. random-effect approach for estimation. In Section...
The Scrivener delivers a comprehensive product from concept to binding. The Scrivener offers research services that use the latest in electronic technology and state-of-the art computer systems. The Scrivener is the only company in the region with an active presence on the Internet. The Internet/...
The theory of small-sample learning [13] has attracted extensive research in recent years. For the problem of small-sample recognition in various fields, researchers have proposed many excellent methods that can be classified as data enhancement, transfer learning, meta learning, and metric learning...
public hydrological datasets that have been used for hydrological research–for example, datasets used by Becket al.32,33, for global model calibration or by Blöschlet al.34for extrapolating climate change impacts on flooding (less than a third of one percent of the daily time series used ...
For the past few years, thanks to the extensive research and improvement of deep learning methods, the task of object detection has achieved unprecedented breakthroughs. Various deep learning based object detection methods [ 1–5 ] have been proposed one after another and gradually replaced ...