Presupposition is the background belief that is known by both the speaker and the addressee, it is tied to particular words and aspects of the surface structure that act as linguistic triggers. The present study aims at investigating whether Iraqi fourth -year university students are able to recognize the English presuppositions through the meaning of these linguistic triggers .To fulfil the basic requirements of the study, the researcher has conducted a test . The results of the study have validated the hypothesis of the work and it is found that the linguistic triggers are important tools in recognizing presuppositions.    

The research's aim is to place two teaching methods ( total and analytical method) and to know which one of them is better than the other in teaching the counter-attack with Epee. The researchers have used the experimental method for being considered suitable to solve the problem of the research. The sample of the research includes third –stage female students of college of physical education and sport sciences / Baghdad University in the subject of fencing, their number amounted 60 female students. It has been used SPSS for processing the results. They have concluded that the two groups of the research and the two methods (( total and analytical) have learnt the counter- attack of the two over mentioned groups. they have recommended to c

The study showed significant differences between the average weight lens and the average amount protein in the lens between that Kestrel Falco tinnunculus L. and the Collared Dove Streptopelia decaocto F. , also the study electrical migration of lens proteins having one bundle of crystalline –? in Kestrel compared with three bundles in Collared Dove, two bundles of crystalline – ? in both , and crystalline – ? appeared as one bundle in both birds.

The tax system, like any other system, as a set of elements and parts that complement each other and are interrelated and interact to achieve specific goals, and is a natural  reflection of the economic, social and political conditions prevailing in society, and therefore the objectives of tax policy formulated in line with the objectives of economic policy in general, which means that any change in economic policy clearly affects fiscal policy measures and fiscal policy in particular.

The problem of searching for the impact of foreign direct investment in the Iraqi tax system was focused on the study  the of foreign direct investment and therole played in developing and improving the economic reality and its implicatio

Polish Academy of Sciences

One of the recent significant but challenging research studies in computational biology and bioinformatics is to unveil protein complexes from protein-protein interaction networks (PPINs). However, the development of a reliable algorithm to detect more complexes with high quality is still ongoing in many studies. The main contribution of this paper is to improve the effectiveness of the well-known modularity density ( ) model when used as a single objective optimization function in the framework of the canonical evolutionary algorithm (EA). To this end, the design of the EA is modified with a gene ontology-based mutation operator, where the aim is to make a positive collaboration between the modularity density model and the proposed

The aim of this research is to apply the concept of total value management to improve the process design of producing the toothpaste in Al Mammon factory one of the in the general company of food industry. The concept of total value management is concerning with achieve more than one values which are important for the customers as these values are related to the customers satisfaction. The research problem is that the factory did not measure the effectiveness of process design as this company has weakness in analyzing this effectiveness in synchronies with total value management. On the other side, the company did not give more attention to the cost of products and selling prices within the value cost/ profit which is one of the

Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c