The presence of hydrocarbons in the soil is considered one of the main problems of pollution. In our current study, eight samples isolated from soil saturated with hydrocarbons were taken from different areas of Baghdad, Iraq. In this study, 5 isolates belonging to Pseudomonas aeruginosa by 99%, 4 isolates to Klebsiella pneumoniae by 98%, and 3 isolates to Enterobacter hormaechei by 97% were diagnosed in different ways. A molecular examination was also conducted by 16sRNA. We recorded P. aeruginosa, K. Pneumoniae and E. hormaechei as new local isolates in NCBI. In addition, a comparison was made between our isolates and the global isolates to determine the degree of convergence in the evolutionary line. The genes alkB and nahAc7 were diagno

The title takes its realistic connotations with its symbols, slogans and historical extensions in Iraq, also, the repercussions of the organic crisis that afflicted it for almost half a century, especially after the abortion of the July 14 Revolution and the spread of the culture of weapons, violence and death that we are living in Iraq nowadays.

The topic is suitable for critical analytical studies carried out by specialists in scientific and academic research centers and cultural institutions because they have an important feasibility at the strategic cultural level in Iraq, the Middle East and the world.

Research in Iraq has fallen to the extreme and is no longer effective, to the extent that it represents a severe cri

This paper describes a newly modified wind turbine ventilator that can achieve highly efficient ventilation. The new modification on the conventional wind turbine ventilator system may be achieved by adding a Savonius wind turbine above the conventional turbine to make it work more efficiently and help spinning faster. Three models of the Savonius wind turbine with 2, 3, and 4 blades' semicircular arcs are proposed to be placed above the conventional turbine of wind ventilator to build a hybrid ventilation turbine. A prototype of room model has been constructed and the hybrid turbine is placed on the head of the room roof. Performance's tests for the hybrid turbine with a different number of blades and different values o

As one type of heating furnaces, the electric heating furnace (EHF) typically suffers from time delay, non-linearity, time-varying parameters, system uncertainties, and harsh en-vironment of the furnace, which significantly deteriorate the temperature control process of the EHF system. In order to achieve accurate and robust temperature tracking performance, an integration of robust state feedback control (RSFC) and a novel sliding mode-based disturbance observer (SMDO) is proposed in this paper, where modeling errors and external disturbances are lumped as a lumped disturbance. To describe the characteristics of the EHF, by using convection laws, an integrated dynamic model is established and identified as an uncertain nonlinear second ord

This paper presents a new algorithm in an important research field which is the semantic word similarity estimation. A new feature-based algorithm is proposed for measuring the word semantic similarity for the Arabic language. It is a highly systematic language where its words exhibit elegant and rigorous logic. The score of sematic similarity between two Arabic words is calculated as a function of their common and total taxonomical features. An Arabic knowledge source is employed for extracting the taxonomical features as a set of all concepts that subsumed the concepts containing the compared words. The previously developed Arabic word benchmark datasets are used for optimizing and evaluating the proposed algorithm. In this paper,

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class