Search results for "PARAMETER"
showing 10 items of 14056 documents
CCDC 1503457: Experimental Crystal Structure Determination
2016
Related Article: Lode De Munck, Carlos Vila, M. Carmen Muñoz, José R. Pedro|2016|Chem.-Eur.J.|22|17590|doi:10.1002/chem.201604606
CCDC 1817831: Experimental Crystal Structure Determination
2018
Related Article: Ondřej Jurček, Hennie Valkenier, Rakesh Puttreddy, Martin Novák, Hazel A. Sparkes, Radek Marek, Kari Rissanen, Anthony P. Davis|2018|Chem.-Eur.J.|24|8178|doi:10.1002/chem.201800537
CCDC 1415863: Experimental Crystal Structure Determination
2016
Related Article: Moritz Schubert, Kathrin Wehming, Anton Kehl, Martin Nieger, Gregor Schnakenburg, Roland Fröhlich, Dieter Schollmeyer, Siegfried R. Waldvogel|2016|Eur.J.Org.Chem.|2016|60|doi:10.1002/ejoc.201501384
CCDC 1814087: Experimental Crystal Structure Determination
2018
Related Article: Attila Márió Remete, Melinda Nonn, Santos Fustero, Matti Haukka, Ferenc Fülöp, Loránd Kiss|2018|Eur.J.Org.Chem.|2018|3735|doi:10.1002/ejoc.201800057
CCDC 1814088: Experimental Crystal Structure Determination
2018
Related Article: Attila Márió Remete, Melinda Nonn, Santos Fustero, Matti Haukka, Ferenc Fülöp, Loránd Kiss|2018|Eur.J.Org.Chem.|2018|3735|doi:10.1002/ejoc.201800057
CCDC 984448: Experimental Crystal Structure Determination
2014
Related Article: Santos Fustero, Javier Miró, María Sánchez-Roselló, Carlos del Pozo|2014|Chem.-Eur.J.|20|14126|doi:10.1002/chem.201403340
Statistical check of USLE-M and USLE-MM to predict bare plot soil loss in two Italian environments
2018
The USLE-M and the USLE-MM estimate event plot soil loss. In both models, the erosivity term is given by the runoff coefficient, QR, times the single-storm erosion index, EI30. In the USLE-MM, QREI30is raised to an exponent b1> 1 whereas b1= 1 is assumed in the USLE-M. Simple linear regression analysis can be applied to parameterize both models, but logarithmically transformed data have to be used for USLE-MM. Parameterizing the USLE-MM with nonlinear regression of untransformed data could be a more appropriate procedure. A statistical check of the two suggested models (USLE-M and USLE-MM), considering two alternative parameterization procedures for the USLE-MM, was carried out for the Mass…
Optimization of Delayed-State Kalman-Filter-based Algorithm via Differential Evolution for Sensorless Control of Induction Motors
2010
This paper proposes the employment of the differential evolution (DE) to offline optimize the covariance matrices of a new reduced delayed-state Kalman-filter (DSKF)-based algorithm which estimates the stator-flux linkage components, in the stationary reference frame, to realize sensorless control of induction motors (IMs). The DSKF-based algorithm uses the derivatives of the stator-flux components as mathematical model and the stator-voltage equations as observation model so that only a vector of four variables has to be offline optimized. Numerical results, carried out using a low-speed training test, show that the proposed DE-based approach is very promising and clearly outperforms a cla…
CCDC 178473: Experimental Crystal Structure Determination
2002
Related Article: M.Horacek, P.Stepnicka, S.Gentil, K.Fejfarova, J.Kubista, N.Pirio, P.Meunier, F.Gallou, L.A.Paquette, K.Mach|2002|J.Organomet.Chem.|656|81|doi:10.1016/S0022-328X(02)01562-0
FLUMO: FLexible Underwater MOdem
2019
The last years have seen a growing interest in underwater acoustic communications because of its applications in marine research, oceanography, marine commercial operations, the offshore oil industry and defense. High-speed communication in the underwater acoustic channel has been challenging because of limited bandwidth, extended multipath, refractive properties of the medium, severe fading, rapid time variation and large Doppler shifts. In this paper, we show an implementation of a flexible Software-Defined Acoustic (SDA) underwater modem, where modulation parameters are completely tunable to optimize performance. In particular, we develop the system architecture following two key ideas. …