Statistical methods and statistical decisions making were used to arrange and analyze the primary data to get norms which are used with Geographic Information Systems (GIS) and spatial analysis programs to identify the animals production and poultry units in strategic nutrition channels, also the priorities of food insecurity through the local production and import when there is no capacity for production. The poultry production is one of the most important commodities that satisfy human body protein requirements, also the most important criteria to measure the development and prosperity of nations. The poultry fields of Babylon Governorate are located in Abi Ghareg and Al_Kifil centers according to many criteria or factors such as the population, production ratio, rivers, distance between fields and streets, and the field's spaces which identify by using TOPSIS method and GIS. TOPSIS and GIS are used to analyze the factors and limiting them to the main factor to know the most important influential factor. These factors consist of the natural and human changes which affect the actual ability to identify the defects according to statistical methods such as the nearest neighbor, the standard distance to build educational data bases aimed to facilitate the information exchange and analysis. The output data of TOPSIS divided into (supreme importance, most important, important, and less important)
A system was used to detect injuries in plant leaves by combining machine learning and the principles of image processing. A small agricultural robot was implemented for fine spraying by identifying infected leaves using image processing technology with four different forward speeds (35, 46, 63 and 80 cm/s). The results revealed that increasing the speed of the agricultural robot led to a decrease in the mount of supplements spraying and a detection percentage of infected plants. They also revealed a decrease in the percentage of supplements spraying by 46.89, 52.94, 63.07 and 76% with different forward speeds compared to the traditional method.
This 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.
The radial wave functions of the cosh potential within the three-body model of (Core+ 2n) have been employed to investigate the ground state properties such as the proton, neutron and matter densities and the associated rms radii of neutron-rich 6He, 11Li, 14Be, and 17B exotic nuclei. The density distributions of the core and two valence (halo) neutrons are described by the radial wave functions of the cosh potential. The obtained results provide the halo structure of the above exotic nuclei. Elastic electron scattering form factors of these halo nuclei are studied by the plane-wave Born approximation.
Artificial lift techniques are a highly effective solution to aid the deterioration of the production especially for mature oil fields, gas lift is one of the oldest and most applied artificial lift methods especially for large oil fields, the gas that is required for injection is quite scarce and expensive resource, optimally allocating the injection rate in each well is a high importance task and not easily applicable. Conventional methods faced some major problems in solving this problem in a network with large number of wells, multi-constrains, multi-objectives, and limited amount of gas. This paper focuses on utilizing the Genetic Algorithm (GA) as a gas lift optimization algorit
The goal (purpose) from using development technology that require mathematical procedure related with high Quality & sufficiency of solving complex problem called Dynamic Programming with in recursive method (forward & backward) through finding series of associated decisions for reliability function of Pareto distribution estimator by using two approach Maximum likelihood & moment .to conclude optimal policy
KA Hadi, AH Asma’a, IJONS, 2018 - Cited by 1
A quantitative description of microstructure governs the characteristics of the material. Various heat and excellent treatments reveal micro-structures when the material is prepared. Depending on the microstructure, mechanical properties like hardness, ductility, strength, toughness, corrosion resistance, etc., also vary. Microstructures are characterized by morphological features like volume fraction of different phases, particle size, etc. Relative volume fractions of the phases must be known to correlate with the mechanical properties. In this work, using image processing techniques, an automated scheme was presented to calculate relative volume fractions of the phases, namely Ferrite, Martensite, and Bainite, present in the
... Show MoreIn this study, the use of non-thermal plasma theory to remove toxic gases emitted from a vehicle was experimentally investigated. A non-thermal plasma reactor was constructed in the form of a cylindrical tube made of Pyrex glass. Two stainless steel rods were placed inside the tube to generate electric discharge and plasma condition, by connecting with a high voltage power supply (up to 40 kV). The reactor was used to remove the contaminants of a 1.25-liter 4-cylinder engine at ambient conditions. Several tests have been carried out for a ranging speed from 750 to 4,500 rpm of the engine and varying voltages from 0 to 32 kV. The gases entering the reactor were examined by a gas analyzer and the gases concentration ratio
... Show MoreSamples of the root nodules were collected to isolate different species of the genus Rhizobium from several leguminous plants; Trigonella foenum-graecum, Medicago sativa, Lens culinaris, Vigna mungo, Vicia faba, Phaseolus vulgaris, and Cicer arietinum, and based on their morphological, cultural, and biochemical characteristics, in addition to the identification of each isolate at the species level by amplified polymerase chain reaction (PCR) and using the sequencing of the nitrogenous bases of the 16S rRNA gene, it was identified as Sinrhizobium meliloti, Sinrhizobium meliloti, Bradyrhizobium elkanii, Rhizobium leguminosarium biovar viciae, Rhizobium leguminosarium biovar phaseoli and Mesorh
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