The experiment was carried out in the spring season of 2017 in the open fields of the College of Agricultural Engineering Sciences/University of Baghdad/Al-Jadriya camps in order to improve the growth and yield of potato plants resulting from the cultivation of true potato seeds of the hybrid BSS-295 by spraying with two organic nutrients. The experiment included two factors: First one was spraying with Megafol nutrient at concentrations 0, 1, 2 and 4 ml l-1 and the second was spraying with Algazone nutrient at concentrations 0, 1.5 and 3 ml l-1, the experiment was applied according to the complete randomized block design with three replications and the averages were compared according to the LSD test 5%. The results indicate that spraying Megafol at a concentration of 4 ml L-1 led to a significant increase in plant height (64.60 cm), and plant yield (214 g plant-1). Spraying Algazone at a concentration of 3 ml L-1 led to a significant increase in plant height (56.47 cm), number of total stems (7.07 stem plant-1), leaf area (0.822 m2 plant-1), number of tubers (9.56 tuber plant-1), and the yield of the plant (144.90 g of plant-1). The interaction between Megafol 4 ml L-1 with Algazone 3 ml L-1 gave the highest value of plant height, number of total branches, chlorophyll content of leaves, tuber weight and plant yield (67.17 cm, 9.15 stem, 374.90 mg 100 g-1, 18.77 g. tuber-1, 235.00 g.plant-1 Respectively).
A mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the others
... Show MoreA mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the
... Show MoreSome cases of common fixed point theory for classes of generalized nonexpansive maps are studied. Also, we show that the Picard-Mann scheme can be employed to approximate the unique solution of a mixed-type Volterra-Fredholm functional nonlinear integral equation.
The Ant System Algorithm (ASA) is a member of the ant colony algorithms family in swarm intelligence methods (part of the Artificial Intelligence field), which is based on the behavior of ants seeking a path and a source of food in their colonies. The aim of This algorithm is to search for an optimal solution for Combinational Optimization Problems (COP) for which is extremely difficult to find solution using the classical methods like linear and non-linear programming methods.
The Ant System Algorithm was used in the management of water resources field in Iraq, specifically for Haditha dam which is one of the most important dams in Iraq. The target is to find out an efficient management system for
... Show MoreThis research discusses application Artificial Neural Network (ANN) and Geographical InformationSystem (GIS) models on water quality of Diyala River using Water Quality Index (WQI). Fourteen water parameterswere used for estimating WQI: pH, Temperature, Dissolved Oxygen, Orthophosphate, Nitrate, Calcium, Magnesium,Total Hardness, Sodium, Sulphate, Chloride, Total Dissolved Solids, Electrical Conductivity and Total Alkalinity.These parameters were provided from the Water Resources Ministryfrom seven stations along the river for the period2011 to 2016. The results of WQI analysis revealed that Diyala River is good to poor at the north of Diyala provincewhile it is poor to very polluted at the south of Baghdad City. The selected parameters wer
... Show MoreIn the present study NiPcTs, CdS thin films, and Blends of NiPcTs:CdS were prepared with 1:2 content mixing ratio of NiPcTs to CdS solutions. Cadmium chloride and thiourea were used as the essential materials for deposition CdS thin films while using organic powder of NiPcTs to deposit NiPcTs nanostructure films. The spin-coating technique was employed to fabricate the NiPcTs , CdS films and NiPcTs-CdS blend. Structural properties of films have been investigated via X-Ray diffraction(XRD),and show that thin films of NiPcTs, and CdS have monoclinic and polycrystalline hexagonal structure respectively while the blend has two polycrystalline structure with cubic and hexagonal phases. Atomic force microscope (AFM) confirmed that the surf
... Show MoreThis article reviews the construction of organic solar cell (OSC) and characterized their optical and electrical properties, where indium tin oxide (ITO) used as a transparent electrode, “Poly (3-hexylthiophene- 2,5-diyl) P3HT / Poly (9,9-dioctylfluorene-alt-benzothiadiazole) F8BT” as an active layer and “Poly(3,4-ethylenedioxythiophene)-poly (styrene sulfonate)” PEDOT: PSS which is referred to the hole transport layer. Spin coating technique was used to prepared polymers thin film layers under ambient atmosphere to make OSC. The prepared samples were characterized after annealing process at (80 ͦ C) for (30 min) under non-isolated circumference. The results show a value of filling factor (FF) of (2.888), (0.233) and (0.28
... Show MoreIn this research, has been to building a multi objective Stochastic Aggregate Production Planning model for General al Mansour company Data with Stochastic demand under changing of market and uncertainty environment in aim to draw strong production plans. The analysis to derive insights on management issues regular and extra labour costs and the costs of maintaining inventories and good policy choice under the influence medium and optimistic adoption of the model of random has adoption form and had adopted two objective functions total cost function (the core) and income and function for a random template priority compared with fixed forms with objective function and the results showed that the model of two phases wit
... Show MoreThis paper deals to how to estimate points non measured spatial data when the number of its terms (sample spatial) a few, that are not preferred for the estimation process, because we also know that whenever if the data is large, the estimation results of the points non measured to be better and thus the variance estimate less, so the idea of this paper is how to take advantage of the data other secondary (auxiliary), which have a strong correlation with the primary data (basic) to be estimated single points of non-measured, as well as measuring the variance estimate, has been the use of technique Co-kriging in this field to build predictions spatial estimation process, and then we applied this idea to real data in th
... Show MoreAbstract :
The study aims at building a mathematical model for the aggregate production planning for Baghdad soft drinks company. The study is based on a set of aggregate planning strategies (Control of working hours, storage level control strategy) for the purpose of exploiting the resources and productive capacities available in an optimal manner and minimizing production costs by using (Matlab) program. The most important finding of the research is the importance of exploiting during the available time of production capacity. In the months when the demand is less than the production capacity available for investment. In the subsequent months when the demand exceeds the available energy and to minimize the use of overti
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