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The zonal statistics tool was then used to assess number of vegetated pixels within each plot.
FVC was calculated by dividing the number of vegetated pixels by the total number of pixels in the AOI.
No, number of samples; min, minimum, max, maximum; SD, standard deviation; and CV, coefficient of variation.
Grain yield prediction using multi-temporal UAV-based multispectral vegetation indices and endmember abundance in rice.

,is widely used in the production of large sized complex thin walled castings in aerospace and automotive manufacturing, and other fields [1] because the parts produced by this method are of high quality, low shrinkage porosity, fine grains, etc.
In recent years, with the rapid development of intelligent control technology, as the representative of the control object in a number of complexes, nonlinear, time-varying and large inertia of the system, fuzzy control intelligent control technology has been widely used.
The fuzzy inference rule is if X1 is A1i and X2 is A2i then Y is Bi (3) where X1 and X2 respectively represent the error and error change rate; Y is the opening output; A1, A2 and B are the fuzzy language value; iis the number of statements, as shown in Table 3.
The total number of rules is 49.
Thus, the results of KP (KI and KD are similar) are Rx,y=i-1n(A1i×A2i)×Bi (4) Defuzzification of output The centroid method is used to implement defuzzification, and the value of the fuzzy control output is given by u*=jkjuj/jkj (5) wherej is the rule number.

Introduction A great number of researches have been conducted on the application of Thermally Stable Diamond Composite (TSDC) in making rock cutting tips [1-7], because TSDC has much higher wear resistance than Tungsten Carbide (WC) [2] and much higher thermal stability than polycrystalline diamond composite (PCD) [3].
The properties of the high thermal stability and wear resistance of TSDC is due to that TSDC is made of synthetic diamond grains using ceramic-based silicon as the binder material during the sintering process [2-3].
Directly estimate the reliability of the tips, R, by calculating the relative frequency of tip failures and using the relationship between the failure probability and reliability: RL=1-FL=ns/Np , (1) where, RL and FL are the reliability and failure probability of the tip after cutting L mm long rock, respectively; ns is the number of the survived tips after cutting L mm long rock and Np is the number of the total tips used in the cutting tests. 3.
Nevertheless, to improve the estimation accuracy, both approaches require a large number of failure data based on accelerated life tests, which are often costly and time-consuming.

At this time, due to the increase in the crystallization rate of amorphous silicon, the number of nanocrystalline Si particles increases and the micro- nanostructures in the surface morphology of the film are mainly clusters of Si nanoparticles (Fig. 2(c)).
At this time, the size of Si particles and the crystallization rate also gradually decrease from the center to the edge of the laser spot area, the grain size of Zone I is 9.2 nm and the crystallization rate is 43.6 %.
When the laser energy is further increased to 600 mJ/cm2, the intensity of Si (111) in the diffraction peak increases to some extent, indicating the number of Si particles increases.
If we continue to apply 600 mJ/cm2 laser energy on a-Si:Al thin film, the crystallization rate of a-Si:Al thin film can further be enhanced, and the number of Si particles increases obviously, while the size of Si particles does not significantly increase (kept at about 10 nm).
It can be understood that with the increase of femtosecond laser energy, the number of crystal silicon particles in a-Si:Al thin film gradually increases, and the refractive index of the thin film as a whole is gradually close to the poly-crystalline silicon, so that the interference peak is gradually suppressed.

Optimization of the grain composition is one of the most widely used methods for modifying the concrete matrix and achieving improved performance characteristics of concretes for various functional purposes [4–7].
The efficiency of reduction of the particle size of the raw material during grinding depends on a number of variables, including the type of mill, the number of revolutions of the mill, the size of the grinding bodies, the volume of the mill filling, the size distribution, the grinding mode (wet or dry), and the hardness of the material [8–11].
Mitrokhin, Fine-grain concrete from mining waste for monolithic construction, IOP Conference Series: Materials Science and Engineering. 327(3) (2018) 032028

A number of theoretical investigations [4-8] have been carried out in the field of fracture mechanics by considering the fractal nature of materials.
In more detail, a finer grained and comparatively ordered material (for example, SF 50 steel in comparison with SCMn 2A steel) presents a lower value of the threshold size TD (as a matter of fact, 2TD < 1TD )
Obviously, the applicability of a self-similar fractal model is confined to the so-called mesoscopic scale range of the material, defined by an upper limit, corresponding to the geometrical sizes of the cracked body, and a lower limit, related to the microstructure of the medium (e.g. aggregate size for concrete, grain size for metals) [8].
Monofractal scaling law for fatigue crack growth The well-known Paris-Erdogan law [30] describes the kinetics of the crack propagation in the intermediate range of IK∆ : m IKC N a ∆= d d , (31) where C and m are material constants, N is the number of fatigue cycles; dNda / and IK∆ are the crack propagation rate and the SIF range, respectively.

In modern analytical investigations which deal with the interaction between titanium and gaseous media, the effects of external parameters (time, temperature, pressure) and internal ones (defects, grain boundaries) are explained differently.
Additional effects upon the gaseous saturation are forced by chemical reactions which take place on the defects of the lattice, on the dislocations and on the grain boundaries.
With respect to the high-temperature interaction between titanium and gaseous media, a number of experimental data reveal that, under special conditions of rarefaction, a new phase is formed on the titanium surface simply by long isothermal exposures [9].
In a number of cases of diffusion saturation of bulky metallic objects by a gaseous impurity, the diffusion zone is appreciably smaller than the thickness of the object.

Macroscopically speaking, AVR is classified as leucocrat, with phaneritic texture of medium to coarse-grain.
SPI is classified as fine grained, non-porfiroid, with two micas but dominantly biotitic, with homogeneous grey/bluish colour [26, 28].
Chosen mesh had a total number of elements of 93,000.
The major limiting factors found in this work for the finite element model are: the computational power required for solving large models with high number of elements (93,000); the assumptions concerning stone heterogeneities (granites were assumed as homogenous and isotropic) that might limit model applicability; the assumptions regarding the use of a linear elastic model which present limitations after the initiation of non-linear behaviour of the materials involved.

Here again, the versatility of the optical characterization allows the observation scale of specimens to be changed by changing the focal length of the camera, the resolution of the images to be increased or decreased by changing the data acquisition frequency of the digital camera (number of images per seconds).
It is also possible to increase the number of image per second if the resolution is lowered.
Namely, it can strongly depend on the microstructure of the alloy substrate, in relation for instance to the crystal orientation of the grain or to the presence of a grain boundary underneath the oxide scale.

INTRODUCTION The study of the soil as a corrosive environment is necessary due to the large number of buried pipelines; their deterioration can represent a real economical and environmental problem through the years.
The X52 steel microstructure consisted of fine pearlite and ferrite with a grain size around 10–20 μ as is shown in Fig. 1.
Low carbon steels tend to have a ferrite–pearlite structure containing little pearlite in the grain boundaries mainly.
It was concluded that the number of ions present in the soil composition is a key factor for the determination of the corrosivity of the soils.