Purpose: To identify the size of the food gap for the main agricultural products and crops in Iraq, which reflects to us the extent to which agricultural production in particular and the agricultural sector in general have declined.Theoretical framework: The theoretical side of the research dealt with the definition of self-sufficiency and the food gap, as well as identifying the reality of agricultural production in Iraq during the study period, as well as the reality of the food gap for the most important agricultural, plant and animal products.Design/methodology/approach: In reviewing the research problem, the researcher adopted the method of deductive and descriptive analysis based on the presentation and detail of official data

Impairment of financial assets defined according to IFRS 9 as the difference between all contractual cash flows that are due to an entity in accordance with the contract and all the cash flows that the entity expects to receive, the entity should estimates all the cash flows through looking to the contract terms during the life time period of the assets or for shorter period if possible, the cash flow should include the amounts of selling any collateral taken or any other enhancement. On the other hand, the Central bank of Iraq guidelines regards impairment differ from the IFRS 9 that’s does not consider the collateral value on calculating the impairment that’s effects on the net profit through recognizing exaggerated loss an

Praise be to Allah, Lord of the Worlds, teach the pen, taught the human what he didn't know, Ihmad - Almighty - and thank him, and repent to him and ask forgiveness, which is the most forgiving, and bear witness that there is no god but Allah alone has no partner, gives and prevents, And I bear witness that Muhammad is  a slave to Allah  and his Messenger, who called for guidance and good speech and spoke, peace be upon him and his family and companions, and those who followed them until the Day of Judgment.

Abstract : 

The aim of the study is to diagnose the level and nature of the relationship between cognitive interactions, cognitive ignorance and the achievement of strategic excellence). The aim of this is to explore theoretical philosophy and intellectual implications of these variables, and, then test the correlation and impact relationships and their feasibility in the application environment, which was formed from the seven directorates in the Ministry of Education. The sample of the study was determined by the directors, their assistants, and the department directors. The sample number is (130). The importance of the study is to come out with a philosophical basis for the nature of the variables, based on an app

Oral swab samples were collected from 120 children (ages between one month- 10 years) who were infected with oral thrush and 30 healthy children. The percentages of isolated yeasts and Bacteria were 66.6% and 96.6% respectively. The dominate yeast and bacteria were Candida albicans and Staphylococcus aureus with of 78.7% and 34.4% respectively. Results revealed that the highest percent of infection with oral thrush disease was 32.5% in children within the age of 1-2 months.

Many objective optimizations (MaOO) algorithms that intends to solve problems with many objectives (MaOP) (i.e., the problem with more than three objectives) are widely used in various areas such as industrial manufacturing, transportation, sustainability, and even in the medical sector.  Various approaches of MaOO algorithms are available and employed to handle different MaOP cases. In contrast, the performance of the MaOO algorithms assesses based on the balance between the convergence and diversity of the non-dominated solutions measured using different evaluation criteria of the quality performance indicators. Although many evaluation criteria are available, yet most of the evaluation and benchmarking of the MaOO with state-of-art a

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob