The force necessary to break the agglomerate (e.g., the adhesion force between two agglomerated crystals) is measured by using two linear variable differential transducers, one of which detects the movement of the moving manipulator and the other one the fiexion of a calibrated fiexible blade.
In this study, we implemented SVMlight Version 6.01 package [ 36] of SVM and learning was carried out by using three (linear, polynomial and radial basis function) kernels.
As long-term meteorological trends can be confounded by both documented and undocumented changes in equipment, land use and location56, we modelled the time series using four linear segments, with three change points to cater for potential discontinuities.
These four conditions were tested using four linear regression models.
Optical anisotropy in the (001) plane of InGaAs nanorods was explored by PPR and PPL using two linear light polarizations, along the [ 1 1 ¯ 0 ] and [110] crystal axes.
Positional effects within the orchard were accounted for by using three different linear mixed models: Model 1: first-order autocorrelation for both row and plant position within the row; Model 2: first-order autocorrelation for only the plant position; Model 3: no autocorrelation for both row and plant position.
Xia et al. [15] have proposed a polynomial root-finding-based method for 2-D DOA estimation by using two parallel uniform linear arrays (ULAs), which has less computational burden.
Statistical analysis was reinforced by using three other nonparametric linear rank tests (Breslow, Peto – Prentice and Tarone – Ware) (Breslow, 1970; Peto and Peto, 1972; Tarone and Ware, 1977; Prentice, 1978).
The PTFs were derived by using three statistical methods: (i) linear regression where there were quantitative input variables, (ii) a regression tree for qualitative, quantitative and mixed types of information and (iii) mean statistics of developer-defined soil groups (class PTF) when only qualitative input parameters were available.
In our framework, we solve the biohash invertibility problem by using two different reconstruction approaches, namely, linear programming [20] and binary iterative hard thresholding [21].
