Results 71 to 80 of about 7,464,686 (281)

Best-first Decision Tree Learning [PDF]

, 2007
In best-first top-down induction of decision trees, the best split is added in each step (e.g. the split that maximally reduces the Gini index). This is in contrast to the standard depth-first traversal of a tree.
Shi, Haijian
core  

Mixed matrix membranes incorporated with size-reduced Cu-BTC for improved gas separation

, 2013
Metal-organic frameworks (MOFs), with large surface area and selective gas adsorption capability, can be the promising additives in mixed matrix membranes (MMMs) for potential gas separation.
Ge, Lei, Rudolph, Victor, Zhou, Wei, Zhu, Zhonghua   +3 more
core   +1 more source

A cooperative Pd-Cu system for direct C-H bond arylation [PDF]

, 2014
The authors are grateful to the Royal Society (University Research Fellowship to CSJC) for financial support.A novel and efficient method for C-H arylation using well-defined Pd- and Cu-NHC systems has been developed.
Cazin, Catherine, Cazin, Catherine S. J., Lesieur, Mathieu, Lazreg, Faima   +3 more
core   +1 more source

Application of Deep Learning-Based Multi-Class Anomaly Detection in Geochemical Exploration with Bayesian Hyperparameter Tuning

Journal of Economic Geology
In this study, 1,238 stream‑sediment samples from the Pariz and Chahargonbad areas of southwestern Kerman Province were analyzed to identify geochemical anomalies.
Puyan Javandel , Nader Fathianpour, Seyed Hassan Tabatabaei   +2 more
doaj   +1 more source

Entropy‐Driven Design of Low‐Melting‐Point Alloys via Compositionally Complex Strategy

Advanced Engineering Materials, EarlyView.
Conventional low‐melting‐point alloys (LMPAs) are limited by a narrow compositional space and inherent property trade‐offs. This review presents an entropy‐driven design strategy that overcomes these limitations, ushering in a new class of low‐melting‐point compositionally complex alloys (LMCCAs).
Yinghui Shang, Jianxiang Zhao, Zhaoqi Chen, Hao Gong, Yinsen Yan, Junlei Tao, Yong Yang   +6 more
wiley   +1 more source

Optimal CU size after coding tree complete traversal for lossless mode with 63% CU size of 16×16, visually lossless mode with 59% CU size of 8×8 and lossy mode with 42% CU size of 32×32.

, 2016
Optimal CU size after coding tree complete traversal for lossless mode with 63% CU size of 16×16, visually lossless mode with 59% CU size of 8×8 and lossy mode with 42% CU size of 32×32.
Yuan Gao (159945), Guandong Gao (2575564), Yueying Wu (747404), Kebin Jia (2575561), Pengyu Liu (2575567)   +4 more
core   +1 more source

Field emission properties of Cu/multiwalled carbon nanotube composite films fabricated by an electrodeposition technique [PDF]

, 2013
Composite films of Cu and multiwalled carbon nanotubes (MWCNTs) were fabricated by an electrodeposition technique, and their field emission properties were examined. Commercially available MWCNTs with various diameters (60-150 nm) were used.
Saito, Takashi, Shinada, Eri, Arai, Susumu   +2 more
core   +1 more source

CU Tenancingo invita al Diplomado en Enología

CU Tenancingo invita al Diplomado en ...
CU, TENANCINGO
core   +1 more source

Controlling Grain Growth in Powder Bed Fusion of Yttria‐Stabilized Zirconia Using Femtosecond Lasers: Challenges and Methodological Insights

Advanced Engineering Materials, EarlyView.
Binder‐free laser powder bed fusion of 8YSZ with a femtosecond laser is used to map process windows linking scan strategy, heat accumulation, and grain growth. Time‐resolved thermography and simulations reveal thermal regimes that enable continuous, vitrified, and fine‐grained 8YSZ surface layers without absorptive additives and demonstrate ...
Markus Kühn, Sarah Kaden, Andrea Barz, Daniel Störzner, Jens Bliedtner, Andrés Fabián Lasagni   +5 more
wiley   +1 more source

Regularized ensemble Kalman inversion for robust and efficient gravity data modeling to identify mineral and ore deposits

Scientific Reports
Modeling mineral and ore bodies from gravity anomalies remains challenging in geophysical exploration due to the ill-posed and non-unique nature of the inverse problem, particularly under conditions of noisy or sparse data. Established inversion methods,
Dharma Arung Laby, S. Sungkono, Arkoprovo Biswas   +2 more
doaj   +1 more source