A Time Synchronous Averaging based method is proposed for processing of the data acquired by proximity probes and its benefit is illustrated on test bearings.
So far, the most commonly used techniques for reducing the impact of noise in the retrieved satellite soil moisture observations have been based on moving average filters and Fourier based methods.
In kernel based methods, the average similarity, S α i, of a test atom x i q with the set of atoms x k q in the training set for class ω α is calculated by comparing x i q with all examples in the training set for ω α as S α i = 1 N α ∑ x k q ∈ ω α K ( x i q, x k q ) (6).
Therefore, simple fixed window based methods like Average and Gaussian filters often fail to produce adequate results [ 10].
In the literature, various methods such as Gaussian filtering, Average filtering and several wavelet transformation based methods have been utilized in spectra de-noising [ 9].
As expected, array-based methods generated fewer but larger CNVs, whereas NGS based methods generated more but, on the average, smaller CNVs.
These centrality measures were compared with other typical centrality measures: Local Average Connectivity- (LAC-) based method, Network Centrality (NC), Subgraph Centrality (SC), and Information Centrality (IC).
The presented method, namely VSIAM3 (Volume/Surface Integrated Average based Multi-Moment Method), employs two integrated moments which are called volume integrated average (VIA) and SIA (Surface Integrated Average), and results in a new finite volume formulation for solving general fluid dynamical problems.
For the combined short-acting methods model, on average (based on MAE), we were able to estimate countries' public-sector CPRs attributable to these short-acting methods to within 1.4 percentage points using the multivariate model and to within 1.9 percentage points using the bivariate model (Table 4).
Table 2 Comparison of the average computation time of different methods Methods The average computation time (s) MSR [11] 0.5398 MSRCR [13] 0.8767 Negative imaging dark channel based method [20] 0.5449 Bright channel prior based method [21] 0.5336 LIME [23] 0.5368 Proposed method 0.6842.
Table 1 Comparison of the average overall quality index of different methods Methods The average overall quality index MSR [11] 0.0576 MSRCR [13] 0.0637 Negative imaging dark channel based method [20] 0.1278 Bright channel prior based method [21] 0.0470 LIME [23] 0.0720 Proposed method 0.1589.
