Results 91 to 100 of about 6,896,512 (318)

Research on the Robustness of Focus Measure Operators Based on RRMSE

Sensors
This paper establishes a quantitative relationship model between the relative root mean square error (RRMSE) and noise parameters under the additive white Gaussian noise model.
Weiying Piao, Chunxue Wang, Yongqi Han
doaj   +1 more source

Root Mean Square Error (RMSE) and coefficient of determination (R2) for different temperature products.

, 2021
Root Mean Square Error (RMSE) and coefficient of determination (R2) for different temperature products.
Jiangyan Gu (11592678), Jun Zhu (84054), Junjie Liu (193511), Zhenzhen Liu (333682), Yu Pan (162493), Fen Qin (4067335), Ziwu Pan (11592675)   +6 more
core   +1 more source

A minimal cellulosome‐like system in Cellulosilyticum lentocellum

FEBS Open Bio, EarlyView.
Cellulose‐degrading bacteria typically use cellulosomes, large multi‐enzyme complexes on a scaffold protein. In Cellulosilyticum lentocellum, we characterise a far smaller arrangement, a single scaffold bound to one cellulase through a single cohesin‐dockerin interaction.
John Allan, Amias Alstrom‐Moore, Gary W Black   +2 more
wiley   +1 more source

Square root kalman filter with contaminated observations [PDF]

, 1992
The algorithm of square root Kalman filtering for the case of contaminated observations is described in the paper. This algorithm is suitable for the parallel computer implementation allowing to treat dynamic linear systems with large number of state ...
Rubio, A., Romera, Rosario, Cipra, Tomas
core   +1 more source

Identification and characterization of a gene conferring stress resistance in Escherichia coli and cyanobacteria

FEBS Open Bio, EarlyView.
Functional screening identified PcSyn14890, a cyanobacteria‐specific protein that enhances growth and stress resistance in E. coli and Synechocystis PCC6803. Although we expected it to function as a molecular chaperone, it was unable to protect against thermal aggregation of GAPDH.
Akiyo Yamada, Takaaki Tanaka, Manaka Uehara, Keigo Nakano, Ken Morishima, Rintaro Inoue, Masaaki Sugiyama, Masafumi Yohda   +7 more
wiley   +1 more source

Correspondence On the Selection of Error Measures for Comparisons Among Forecasting Methods [PDF]

Clements and Hendry (1993) proposed the Generalized Forecast Error Second Moment (GFESM) as an improvement to the Mean Square Error in comparing forecasting performance across data series.
JS Armstrong, Robert Fildes
core  

The normalized root mean square error in Fig. 3.

, 2015
The normalized root mean square error in Fig. 3.
Ming Jiang (11433), Jian Fu (41067), Xinhua Hu (511621), Franz Pfeiffer (288057), Astrid Velroyen (641814), Martin Bech (288040)   +5 more
core   +1 more source

Multiple Sclerosis Relapse Activity After Ozanimod Discontinuation in DAYBREAK Trial Participants

Annals of Clinical and Translational Neurology, EarlyView.
Multiple Sclerosis Relapse Activity After Ozanimod Discontinuation in DAYBREAK Trial Participants. ABSTRACT Objective Return of disease activity is expected when patients discontinue disease‐modifying therapy (DMT) for multiple sclerosis (MS). Some MS DMTs are associated with higher‐than‐expected disease activity (rebound) after discontinuation.
Ralf Gold, Krzysztof W. Selmaj, Regina Berkovich, Jeffrey A. Cohen, Giancarlo Comi, Eva K. Havrdová, James K. Sheffield, Hetal Desai, Chun‐Yen Cheng, Jon V. Riolo, Andrew Thorpe, Erik DeBoer, Bruce A. C. Cree   +12 more
wiley   +1 more source

Application of Near Infrared Spectroscopy for Quality Monitoring and Controlling in the Formulation Process of Simvastatin Tablets

工程科学与技术, 2015
:Near infrared spectroscopy (NIR) technology with chemometric techniques was applied to fast analyze various parameters in the process of Simvastatin tablets producing.The four parameters including water content,compression force,tablet hardness and ...
林翔, 彭熙琳, 陈晓春, 李晖
doaj  

The root-mean-square error (RMSE) for effect of cell distribution and cell lag on the model fit to experimental data (cells/cm²).

, 2018
The root-mean-square error (RMSE) for effect of cell distribution and cell lag on the model fit to experimental data (cells/cm2).
William B. Lott (206536), Michael J. Osiecki (837098), Sean D. L. McElwain (5687690)   +2 more
core   +1 more source