The objective of this study is to attempt to provide a quantitative analysis to the causes of unemployment  in Iraq and its mechanisms of generation, as well as a review of the most important  types of both visible and invisible unemployment, and an attempt to measure the disguised  unemployment  and analyze the causes. The problem of the research lies in the fact that the Iraqi Economy has been suffered  for  a long time although its characterized by abundant  physical and natural  resources, from the existence of the  phenomenon of unemployment  in the previous two types. Causing a lot of economic problems, represented by the great waste of resources and

Abstract

       Although the subject of biofuels industry is linked directly to the energy sector, but has links and numerous indirect effects, in particular effects on the environment and agriculture, this study (opportunities and challenges of biofuels industry and impact on the development of the agricultural sector in developing countries) a modest step to identify the industry in detail and identify the types of products and raw materials entering, then define or limit the positive and negative impacts of this industry in General and for specific products In particular, detailed, and then flip all those effects on the agricultural sector in developing countries can benef

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

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 object under de

Two novel demountable shear connectors for precast steel-concrete composite bridges are presented. The connectors use high-strength steel bolts, which are fastened to the steel beam with the aid of a special locking configuration that prevents slip of bolts within their holes. Moreover, the connectors promote accelerated construction and overcome typical construction tolerances issues of precast structures. Most importantly, the connectors allow bridge disassembly, and therefore, can address different bridge deterioration scenarios with minimum disturbance to traffic flow, i.e. (1) precast deck panels can be rapidly uplifted and replaced; (2) connectors can be rapidly removed and replaced; and (3) steel beams can be replaced, while precast

Several correlations have been proposed for bubble point pressure, however, the correlations could not predict bubble point pressure accurately over the wide range of operating conditions. This study presents Artificial Neural Network (ANN) model for predicting the bubble point pressure especially for oil fields in Iraq. The most affecting parameters were used as the input layer to the network. Those were reservoir temperature, oil gravity, solution gas-oil ratio and gas relative density. The model was developed using 104 real data points collected from Iraqi reservoirs. The data was divided into two groups: the first was used to train the ANN model, and the second was used to test the model to evaluate their accuracy and trend stability

The study focuses on the problem that Iraq is approaching an increasing rate of literacy;the available data refers to a rate of (18% -19%). In addition to the fact that the generalcurrent role of the programs directed to literacy is not actually effective enough to limit the expansion of this rate.

The importance of this study highlights the fact that the Iraqi universities are an important tributary among the tributaries of human development, especially in spreading the education of the voluntary work in literacy field and confirming the connection between the students and their society and their role in solving one of the prominent challenges that face the development, i.e., literacy.

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