There is no doubt that Agricultural Policy is the main responsible for the degrading in Agricultural sector in Iraq during the period 2003-2013, and that was very clear from magnitude of indicators because of little sharing of each of agricultural product in GDP because it was (9.38%) in average during the study period and the annual changing of it was negative (-5.82%), and there is increasing in deficit of trade balance in Agriculture during the study period about (4185.73) million US$, and the percentage of agricultural exports from total exports was (0.14%) in average only. The foreign trade policy in Agricultural products also cannot determine map of Revealed Comparative Advantage (RCA) of Agricultural products and crops. The study sh

                Inflation is one of the important issues that the economic authorities in all countries of the world care about, where the loss of money for its function is one of the most important and largest inflationary effects that this phenomenon leaves on the economy, and Iraq, like other countries, has had its share of the problem of inflation for a long time due to the circumstances that He went through it, whether it was the wars he fought or the economic blockade that was imposed on him in the nineties of the last century. Economically, the problem of inflation is addressed through the use of fiscal policy tools, including tax increases in order to abso

Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

            The objective of this study is to measure the impact of financial development on economic growth in Iraq over the period (2004-2018) by applying a fully corrected square model (FMOLS) Whereas, a set of variables represented by (credit-to-private ratio of GDP, the ratio of money supply in the broad sense of GDP, percentage of bank deposits from GDP) were chosen as indicators for measuring financial development and GDP to measure economic growth.

Major tests have been carried out, such as the stability test (Unite Root Test), the integration test (Cointegration). Results of the study showed that there

To assess the contribution of Doppler broadening and examine the
Compton profile, the Compton energy absorption cross sections are
measured and calculated using formulas based on a relativistic
impulse approximation. The Compton energy-absorption cross
sections are evaluated for different elements (Fe, Zn, Ag, Au and Hg)
and for a photon energy range (1 - 100 keV). With using these crosssections,
the Compton component of the mass–energy absorption
coefficient was derived, where the electron momentum prior to the
scattering event caused a Doppler broadening of the Compton line.
Also, the momentum resolution function was evaluated in terms of
incident and scattered photon energy and scattering angle. The res

The aim of this study is to develop a novel framework for managing risks in smart supply chains by enhancing business continuity and resilience against potential disruptions. This research addresses the growing uncertainty in supply chain environments, driven by both natural phenomena-such as pandemics and earthquakes—and human-induced events, including wars, political upheavals, and societal transformations. Recognizing that traditional risk management approaches are insufficient in such dynamic contexts, the study proposes an adaptive framework that integrates proactive and remedial measures for effective risk mitigation. A fuzzy risk matrix is employed to assess and analyze uncertainties, facilitating the identification of disr