The purpose of this experiment was to determine the relationship between the path coefficient and seed rate for four different barley cultivars (Amal, Ibaa 265, Ibaa 99, and Buhooth 244) during the 2019-2020 winter season. The experiment was carried out using a split plot design with three replications according to a randomized complete block design (RCBD). The highest positive thru effect on grain yield was found for flag leaf area and harvest index at aseeding rate of 130 kg.h-1; the highest positive direct effect on grain yield was found for flag leaf area and plant height at aseeding rate of 160 kg.h-1; and the highest positive direct effect on yield was found for biological yield and harvest index at a seeding rate of 190 kg.ha-1. Because of this, it can be used as proof of selective breeding for increased yield in barley by plant breeders.
The Bi2Se3 compound was synthesis by fusing initial compounds consisting of
extra pure elements in stoichiometric ratio from elements compound, charged inside
quartz ampoule. The crystal growth of Bi2Se3 carried out using Brighaman technique
process from melting f (Bi+Se ) at temperature of 810 ºC for about 48 hrs. Single crystal
of Bi2Se3 has been grown in direction (211) after slow cooling on account of heat
gradient to zone furnaces at cooling rate (1-3) C/hr. The structure study of the compound
was determined by x-ray diffraction technique, which it has bismuthinite structure and
orthorhombic unit cell with lattice parameters of a=10.2678 Å, b=11.2392 Å and
c=5.1737 Å
Pushover analysis is an efficient method for the seismic evaluation of buildings under severe earthquakes. This paper aims to develop and verify the pushover analysis methodology for reinforced concrete frames. This technique depends on a nonlinear representation of the structure by using SAP2000 software. The properties of plastic hinges will be defined by generating the moment-curvature analysis for all the frame sections (beams and columns). The verification of the technique above was compared with the previous study for two-dimensional frames (4-and 7-story frames). The former study leaned on automatic identification of positive and negative moments, where the concrete sections and steel reinforcement quantities the
... Show MoreBackground: Dental implants provide a unique treatment modality for the replacement of lost dentition .This is accomplished by the insertion of relatively inert material (a biomaterial) into the soft and hard tissue of the jaws, there by providing support and retention for dental prostheses. Low level laser therapy (LLLT) is an effective tool used to prompt bone repair and modeling post surgery; this has referred to the biostimulation effect of LLLT. The aims of this study were to evaluate the immmunohistochemical expression of vascular endothelial growth factor (VEGF) and transforming growth factor -beta (TGF-β) in experimental and control groups with mechanical test. Materials and Methods: Thirty two adult New Zealand white rabbits use
... Show MoreAmong the different passive techniques heat pipe heat exchanger (HPHE) seems to be the most effective one for energy saving in heating ventilation and air conditioning system (HVAC). The applications for nanofluids with high conductivity are favorable to increase the thermal performance in HPHE. Even though the nanofluid has the higher heat conduction coefficient that dispels more heat theoretically but the higher concentration will make clustering .Clustering is a problem that must be solved before nanofluids can be considered for long-term practical uses. Results showed that the maximum value of relative power is 0.13 mW at nanofluid compared with other concentrations due to the low density of nanofluid at this concentration. For highe
... Show MoreIn this paper, the Reliability Analysis with utilizing a Monte Carlo simulation (MCS) process was conducted on the equation of the collapse potential predicted by ANN to study its reliability when utilized in a situation of soil that has uncertainty in its properties. The prediction equation utilized in this study was developed previously by the authors. The probabilities of failure were then plotted against a range of uncertainties expressed in terms of coefficient of variation. As a result of reliability analysis, it was found that the collapse potential equation showed a high degree of reliability in case of uncertainty in gypseous sandy soil properties within the specified coefficient of variation (COV) for each property. When t
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The objective of this study was to develop neural network algorithm, (Multilayer Perceptron), based correlations for the prediction overall volumetric mass-transfer coefficient (kLa), in slurry bubble column for gas-liquid-solid systems. The Multilayer Perceptron is a novel technique based on the feature generation approach using back propagation neural network. Measurements of overall volumetric mass transfer coefficient were made with the air - Water, air - Glycerin and air - Alcohol systems as the liquid phase in bubble column of 0.15 m diameter. For operation with gas velocity in the range 0-20 cm/sec, the overall volumetric mass transfer coefficient was found to decrease w
... Show MoreThis paper is focused on orthogonal function approximation technique FAT-based adaptive backstepping control of a geared DC motor coupled with a rotational mechanical component. It is assumed that all parameters of the actuator are unknown including the torque-current constant (i.e., unknown input coefficient) and hence a control system with three motor control modes is proposed: 1) motor torque control mode, 2) motor current control mode, and 3) motor voltage control mode. The proposed control algorithm is a powerful tool to control a dynamic system with an unknown input coefficient. Each uncertain parameter/term is represented by a linear combination of weighting and orthogonal basis function vectors. Chebyshev polynomial is used
... Show MoreIn recent years, the world witnessed a rapid growth in attacks on the internet which resulted in deficiencies in networks performances. The growth was in both quantity and versatility of the attacks. To cope with this, new detection techniques are required especially the ones that use Artificial Intelligence techniques such as machine learning based intrusion detection and prevention systems. Many machine learning models are used to deal with intrusion detection and each has its own pros and cons and this is where this paper falls in, performance analysis of different Machine Learning Models for Intrusion Detection Systems based on supervised machine learning algorithms. Using Python Scikit-Learn library KNN, Support Ve
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