| 1 |
Modeling and Parameter Identification foraBiofilm in a Microbial Fuel Cell
Kubannek F, Krewer U
Chemie Ingenieur Technik, 91(6), 856, 2019 |
| 2 |
Determining the number of segments for piece-wise linear representation of discrete-time signals
Wang JD, Yu Y, Chen K
Computers & Chemical Engineering, 120, 46, 2019 |
| 3 |
Confidence interval computation method for dynamic performance evaluations of solar thermal collectors
Zirkel-Hofer A, Perry S, Kramer K, Heimsath A, Scholl S, Platzer W
Solar Energy, 162, 585, 2018 |
| 4 |
To be certain about the uncertainty: Bayesian statistics for C-13 metabolic flux analysis
Theorell A, Leweke S, Wiechert W, Noh K
Biotechnology and Bioengineering, 114(11), 2668, 2017 |
| 5 |
Compressibility of unvulcanized natural and EPDM rubber: New experimental protocol and data evaluation in the framework of large strain elasticity theory
Plachy R, Scheiner S, Luczynski KW, Holzner A, Hellmich C
Polymer, 123, 334, 2017 |
| 6 |
CO-PrOx over nano-Au/TiO2: Monolithic catalyst performance and empirical kinetic model fitting
Moreno MS, Lopez E, Adrover ME, Divins NJ, Llorca J
International Journal of Hydrogen Energy, 41(47), 22043, 2016 |
| 7 |
Energy Performance Certificate of building and confidence interval in assessment: An Italian case study
Tronchin L, Fabbri K
Energy Policy, 48, 176, 2012 |
| 8 |
Evaluation of realistic 95% confidence intervals for the activation energy calculated by the iterative linear integral isoconversional method
Cai JM, Han D, Chen Y, Chen SY
Chemical Engineering Science, 66(12), 2879, 2011 |
| 9 |
Confidence interval estimation under the presence of non-Gaussian random errors: Applications to uncertainty analysis of chemical processes and simulation
Vasquez VR, Whiting WB, Meerschaert MM
Computers & Chemical Engineering, 34(3), 298, 2010 |
| 10 |
Quantifying the effects of co-expressing EGFR and HER2 on HER activation and trafficking
Shankaran H, Zhang Y, Opresko L, Resat H
Biochemical and Biophysical Research Communications, 371(2), 220, 2008 |
