Soil compaction is one of the most harmful elements affecting soil structure, limiting plant growth and agricultural productivity. It is crucial to assess the degree of soil penetration resistance to discover solutions to the harmful consequences of compaction. In order to obtain the appropriate value, using soil cone penetration requires time and labor-intensive measurements. Currently, satellite technologies, electronic measurement control systems, and computer software help to measure soil penetration resistance quickly and easily within the precision agriculture applications approach. The quantitative relationships between soil properties and the factors affecting their diversity contribute to digital soil mapping. Digital soil maps use machine learning algorithms to determine the above relationship. Algorithms include multiple linear regression (MLR), k-nearest neighbors (KNN), support vector regression (SVR), cubist, random forest (RF), and artificial neural networks (ANN). Machine learning made it possible to predict soil penetration resistance from huge sets of environmental data obtained from onboard sensors on satellites and other sources to produce digital soil maps based on classification and slope, but whose output must be verified if they are to be trusted. This review presents soil penetration resistance measurement systems, new technological developments in measurement systems, and the contribution of precision agriculture techniques and machine learning algorithms to soil penetration resistance measurement and prediction.
To expedite the learning process, a group of algorithms known as parallel machine learning algorithmscan be executed simultaneously on several computers or processors. As data grows in both size andcomplexity, and as businesses seek efficient ways to mine that data for insights, algorithms like thesewill become increasingly crucial. Data parallelism, model parallelism, and hybrid techniques are justsome of the methods described in this article for speeding up machine learning algorithms. We alsocover the benefits and threats associated with parallel machine learning, such as data splitting,communication, and scalability. We compare how well various methods perform on a variety ofmachine learning tasks and datasets, and we talk abo
... Show MoreThe current research reports the preparation and fabrication of the silver paste conductor which is employed as a soldering material for electro – optical components ohmic interconnections. The prepared paste possesses electrical characteristics identical to the ohmic connectors as its observable from resistance – temperature variation. Moreover, the I – V characteristics obeys Ohm’s law and this dependency was further confirmed by the nearly constant capacitance measurements with voltage and frequency. A noticeable improvement in electrical conductivity, compared to the pure silver paste sample, was noted for samples prepared by mixing predetermined weight ratios of brass and copper. Furthermore, stability of electrical resistan
... Show MoreThe focus of this paper is the presentation of a new type of mapping called projection Jungck zn- Suzuki generalized and also defining new algorithms of various types (one-step and two-step algorithms) (projection Jungck-normal N algorithm, projection Jungck-Picard algorithm, projection Jungck-Krasnoselskii algorithm, and projection Jungck-Thianwan algorithm). The convergence of these algorithms has been studied, and it was discovered that they all converge to a fixed point. Furthermore, using the previous three conditions for the lemma, we demonstrated that the difference between any two sequences is zero. These algorithms' stability was demonstrated using projection Jungck Suzuki generalized mapping. In contrast, the rate of convergenc
... Show MoreABSTRACT
The multi-drug resistant efflux pump is a glycoprotein pump whose function is to push foreign substances. The efflux pump is found in humans, animals. It also has wide-ranging properties in bacteria and fungi. They are found in all species of bacteria, and efflux pump genes can be found in bacterial chromosomes or mobile genetic elements, such as plasmids. The most sensitive function that leads to a global problem is its resistance to antibiotics in bacterial cells, which increases the ability to bacteria from becoming strong virulence factors that most or all antibiotics cannot kill. It also has othe
... Show MoreThe childhood stage is considered the most important stage of all the stages through
the human being’s life. In this stage the human being will be more affected by the various
factors that surround him/her. The first five years of his/her life leave a great impact not only
on the human being personality, but also on his/her whole life. Therefore, it is worthwhile tobe concerned with and focus at the raising up and the teaching of the child during the
childhood stage.
The mission of raising up children in this era - the era of globalization and information
bursting or news flooding – has become a very difficult or even an impossible mission.
Furthermore, not only in the Arabic world, but also all over the world, t
Eight soil samples were selected around Najaf governorate at depth levels 40-50 cm. X-Ray Fluorescence (XRF) was used to determine the concentrations of major and trace elements. Liner and mass attenuation coefï¬cient (µ, µÏ) have been determined at gamma energies (662, 1172,1332) keV using NaI (Tl) detector. The range of linear attenuation coefficients for calculated samples were (0.553-1.163) cm-1, (0.122-0.178) cm-1 and (0.049-0.105) cm-1 at (662, 1172,1332) keV respectively. The range of mass attenuation coefficients obtained (0.39-0.76) cm2/gm, (0.087-0.117) cm2/gm and (0.0336-0.074) cm2/gm at (662, 1172,1332) keV respectively. The result
... Show MoreThis paper provides an attempt for modeling rate of penetration (ROP) for an Iraqi oil field with aid of mud logging data. Data of Umm Radhuma formation was selected for this modeling. These data include weight on bit, rotary speed, flow rate and mud density. A statistical approach was applied on these data for improving rate of penetration modeling. As result, an empirical linear ROP model has been developed with good fitness when compared with actual data. Also, a nonlinear regression analysis of different forms was attempted, and the results showed that the power model has good predicting capability with respect to other forms.
Objective: To investigate the relation between dyslipidemia and insulin resistance where it is one of the metabolic
disorders in patients with type-ΙΙ diabetes mellitus and compare the results with the control group.
Methodology: Blood samples were collected from (35) patients with type-ΙΙ diabetes mellitus, besides (35) healthy
individuals as a control group were enrolled in this study. The age of all subjects range from (20-50). Serum was
used in determination of glucose, insulin, lipid profile (cholesterol (Ch), triglyceride (TG), high-density lipoprotein
(HDL-Ch), low-density lipoprotein (LDL-Ch) and very low-density lipoprotein (VLDL), for patients and control
groups. Insulin resistance (IR) was calculated acco
This study introduced the effect of using magnetic abrasive finishing method (MAF) for finishing flat surfaces. The results of experiment allow considering the MAF method as a perspective for finishing flat surfaces, forming optimum physical mechanical properties of surfaces layer, removing the defective layers and decreasing the height of micro irregularities. Study the characteristics which permit judgment parameters of surface quality after MAF method then comparative with grinding