The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Convolutional Neural Network (CNN) has been chosen as a better option for the training process because it produces a high accuracy. The final accuracy has reached 91.18% in five different classes. The results are discussed in terms of the probability of accuracy for each class in the image classification in percentage. Cats class got 99.6 %, while houses class got 100 %.Other types of classes were with an average score of 90 % and above.
Background: Neural tube defects (NTDs) are said to be inherited in a multifactorial fashion, i.e. genetic-environmental interaction. Maternal nutritional deficiencies had long been reported to cause NTDs, especially folate deficiency during early pregnancy. More attention had been paid to the exact mechanism by which this deficiency state causes these defects in the developing embryo. The most significant of all researches was that connecting reduced folate and increased homocysteine level in maternal serum on one hand and the risk of developing a NTD baby on the other hand. Objectives : to determine the significance of homocysteine level in Iraqi mothers who gave birth to babies with NTDs as compared to normal controls. Patients, Materials
... Show MoreThis work examines numerically the effects of particle size, particle thermal conductivity and inlet velocity of forced convection heat transfer in uniformly heated packed duct. Four packing material (Aluminum, Alumina, Glass and Nylon) with range of thermal conductivity (from200 W/m.K for Aluminum to 0.23 W/m.K for Nylon), four particle diameters (1, 3, 5 and 7 cm), inlet velocity ( 0.07, 0.19 and 0.32 m/s) and constant heat flux ( 1000, 2000 and 3000 W/ m 2) were investigated. Results showed that heat transfer (average Nusselt number Nuav) increased with increasing packing conductivity; inlet velocity and heat flux, but decreased with increasing particle size.Also, Aluminum average Nusselt number is about (0.85,2.
... Show MoreThe behavior and shear strength of full-scale (T-section) reinforced concrete deep beams, designed according to the strut-and-tie approach of ACI Code-19 specifications, with various large web openings were investigated in this paper. A total of 7 deep beam specimens with identical shear span-to-depth ratios have been tested under mid-span concentrated load applied monotonically until beam failure. The main variables studied were the effects of width and depth of the web openings on deep beam performance. Experimental data results were calibrated with the strut-and-tie approach, adopted by ACI 318-19 code for the design of deep beams. The provided strut-and-tie design model in ACI 318-19 code provision was assessed and found to be u
... Show MoreTransportation network could be considered as a function of the developmental level of the Iraq, that it is representing the sensitive nerve of the economic activity and the corner stone for the implementation of development plans and developing the spatial structure.
The main theme of this search is to show the characteristics of the regional transportation network in Iraq and to determine the most important effective spatial characteristics and the dimension of that effect negatively or positively. Further this search tries to draw an imagination for the connection between network as a spatial phenomenon and the surrounded natural and human variables within the spatial structure. This search aiming also to determine the nat
Mass transfer was examined at a stationary rectangular copper electrode (cathode) by using the reduction of cupric ions as the electrochemical reaction. The influence of electrolyte temperature (25, 45, and 65 oC), and cupric ions concentration (4, 8, and 12 mM) on mass transfer coefficient were investigated by using limiting current technique. The mass transfer coefficient and hence the Sherwood number was correlated as Sh =
A paraffin wax and copper foam matrix were used as a thermal energy storage material in the double passes air solar chimney (SC) collector to get ventilation effect through daytime and after sunset. Air SC collector was installed in the south wall of an insulated test room and tested with different working angles (30o, 45o and 60o). Different SC types were used; single pass, double passes flat plate collector and double pass thermal energy storage box collector (TESB). A computational model based on the finite volume method for transient tw dimensional domains was carried out to describe the heat transfer and storage in the thermal energy storage material of collector. Also, equivalent specific heat metho
... Show MorePlane cubics curves may be classified up to isomorphism or projective equivalence. In this paper, the inequivalent elliptic cubic curves which are non-singular plane cubic curves have been classified projectively over the finite field of order nineteen, and determined if they are complete or incomplete as arcs of degree three. Also, the maximum size of a complete elliptic curve that can be constructed from each incomplete elliptic curve are given.
Numerical investigation has been carried out on heat transfer and friction factor characteristics of copper-water nanofluid flow in a constant heat-fluxed tube with the existence of new configuration of vortex generator using Computational Fluid Dynamics (CFD) simulation. Two types of swirl flow generator: Classical twisted tape (CTT) and Parabolic-cut twisted tape (PCT) with a different twist ratio (= 2.93, 3.91 and 4.89) and different cut depth (= 0.5, 1.0 and 1.5 cm) with 2% and 4% volume concentration
... Show MoreMachine learning has a significant advantage for many difficulties in the oil and gas industry, especially when it comes to resolving complex challenges in reservoir characterization. Permeability is one of the most difficult petrophysical parameters to predict using conventional logging techniques. Clarifications of the work flow methodology are presented alongside comprehensive models in this study. The purpose of this study is to provide a more robust technique for predicting permeability; previous studies on the Bazirgan field have attempted to do so, but their estimates have been vague, and the methods they give are obsolete and do not make any concessions to the real or rigid in order to solve the permeability computation. To
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