The current research (technical mediator in contemporary Iraqi painting) dealt with the concept of technical mediator in contemporary arts and its role in the qualitative transformation in art, the diversity of discoveries in technical media that artists use in their artistic achievement, and the extent of their impact on contemporary Iraqi painting, where the research problem was identified (what is The nature and role of technical media in showing works in contemporary Iraqi painting) and (What are the intellectual and aesthetic concepts of media and techniques as references for contemporary art in Iraq). The second topic dealt with technical media and their impact on the plastic arts, and the third topic focused on the technical med

The Tel Hajar formation in the studied area has been divided into five microfacics units:

1) Fine hiogenic dolomite facies.

2) Sandy rich dolomite facies.

3) Dolomite diagenetic facies.

4) Recrystal1ized wackestone in microfacies.

5) Mudsione facies.

Microfacics reflect shallow marine water with open Circulation in the lower part of the formation and the environment of the upper is enclosed between upper tide and tide. The most important diagenesis was recrystallization and spary calcite deposit inside fossils chambers and pores.

In petroleum industry, the early knowledge of “pore pressure gradient” is the basis in well design and the extraction of these information is more direct when the pore pressure gradient is equal to normal gradient; however, this matter will be more complex if it deviate from that limit which is called “abnormal pore pressure”, if this variable does not put in consideration, then many drilling problems will occur might lead to entire hole loss. To estimate the pore pressure gradient there are several methods, in this study; Eaton method’s is selected to extract the underground pressure program using drilling data (normalized rate of penetration) and logs data (sonic and density log). The results shows that an abnormal high press

This paper deals with the description of the system of formation and derivation of words in the Russian language. In this work, we will present recent trends in the study of the Russian language that deal with vocabulary formation. The lexical system of the Russian language is associated with a common (or opposite) meaning; similar (or opposite) in stylistic characteristics; united by a common type of word formation; related to a common descent and belonging to a vocabulary of much or little use, etc. The results of the most prominent linguists and specialists who dealt with this topic will be presented, in addition to presenting their different views on word formation. The words of the Russian language consist of mor vimat that participate

Shiranish formation has been divided into two microfacies units: 1 - Many biowackestone facies and 2 - maly packstone using planktonic foraminifera and other carbonate components in the rock cutting and core slides. Microfacies reflect marin deep shelf margin in the lower part of the formation, the upper part was deeper. The thickness of the formation is determined, depending on addition to the presence of echinoderm framents debris and spines. This is in disagreement with the 195 ft thickness reported by the Oil Exploration Company The age of the formation is estimated depending on the recognized biostratigraphic zone using the index fossils to be Upper - Middle Mastrichtion.

Nanoparticles have gained considerable interest in recent times for oil recovery purposes owing to significant capabilities in wettability alteration of reservoir rocks. Wettability is a key factor controlling displacement efficiency and ultimate recovery of oil. The present study investigates the influence of zirconium (IV) oxide (ZrO2) and nickel (II) oxide (NiO) nanoparticles on the wetting preference of fractured (oil-wet) limestone formations. Wettability was assessed through SEM, AFM and contact angle. The potentials of the nanoparticles to alter oil-wet calcite substrates water wet, was experimentally tested at low nanoparticle concentrations (0.004–0.05 wt%). Quite similar behaviour was observed for both nanoparticles at the same

A new method for determination of allopurinol in microgram level depending on its ability to reduce the yellow absorption spectrum of (I-3) at maximum wavelength ( ?max 350nm) . The optimum conditions such as "concentration of reactant materials , time of sitting and order of addition were studied to get a high sensitivity ( ? = 27229 l.mole-1.cm-1) sandal sensitivity : 0.0053 µg cm-2 ,with wide range of calibration curve ( 1 – 9 µg.ml-1 ) good stability (more then24 hr.) and repeatability ( RSD % : 2.1 -2.6 % ) , the Recovery % : ( 98.17 – 100.5 % ) , the Erel % ( 0.50 -1.83 % ) and the interference's of Xanthine , Cystein , Creatinine , Urea and the Glucose in 20 , 40 , 60 fold of analyate were also studied .

This 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 Nu_av) 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.

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 Conv

     Community detection is an important and interesting topic for better understanding and analyzing complex network structures. Detecting hidden partitions in complex networks is proven to be an NP-hard problem that may not be accurately resolved using traditional methods. So it is solved using evolutionary computation methods and modeled in the literature as an optimization problem.  In recent years, many researchers have directed their research efforts toward addressing the problem of community structure detection by developing different algorithms and making use of single-objective optimization methods. In this study, we have continued that research line by improving the Particle Swarm Optimization (PSO) algorithm using a