RMA is an algorithm used to create an expression matrix from Affymetrix data. The raw intensity values are background corrected, log2 transformed and then quantile normalized. Next a linear model is fit to the normalized data to obtain an expression measure for each probe set on each array. ...
MBCB - Robust Multi-Array Average Background Correction for Illumina BeadarrayYang XieMin ChenJeff Allen
developed by Affymetrix [1]. It is the algorithm that, for instance, was most frequently applied within the framework of phase II of the microarray quality control (MAQC) project [2].
array would be produce by: // y = (Index(x) / 2) - 0 // Where Index(x) is the index of the bin to which x belongs // Bins upper bounds are: 4.5 7 ∞ var fixZeroParams = normalizeFixZeroTransform .GetNormalizerModelParameters(0) as BinNormalizerModelParameters< ImmutableArray<...
Despite effective, FedSGD is computationally expensive since each client has to communicate twice with the central server after every SGD step. To tackle this drawback, McMahan et al. (2017) propose the Federated Average (FedAvg) algorithm. FedAvg reduces the communication overhead by allowing mult...
An overview of our ACS-DCF algorithm is depicted in Fig. 1. To the best of our knowledge, this is the first study introducing adaptive channel selection in the formulation of DCF-based visual object tracking. It reduces the number of feature channels by structured regularisation using an ...
(8)vik+1=ωvik+c1r1(xi,pbestk−xik)+c2r2(xi,gbestk−xik)where ω, c1, andc2 are the weight parameters affecting the performance of the algorithm. r1 and r2 are random numbers sampled from the uniform distribution [0,1]. In this study, we set the weight parameters as 0.729, ...
Finally, machine intelligence was realized by introducing ANN algorithm to a sensor-integrated origami robot, which demonstrated autonomous robot navigation with high-accuracy trajectory prediction, and surrounding awareness navigation. Fig. 7: Computational design of ultra-robust strain sensors for ...
When we use robust measures with linear combinations of the median, quartile deviation, midrange, interquartile range, and quartile average of the supplementary variable in (23), we get different series of estimators such as Ti(d)N⊖, Ti(d)N⊕, Ti(d)N⊗, Ti(d)N⊛ and Ti(d)N...
However, the numerical processing of chance constraints is computationally very hard. The first difficulty in handling CCPs is that calculating the joint probability may require a multidimensional integration. A commonly used approach to handle this issue is sample average approximation (SAA). SAA offers...