This study aims to measure and analyze the direct and indirect effects of the financial variables, namely (public spending, public revenues, internal debt, and external debt), on the non-oil productive sectors with and without bank credit as an intermediate variable, using quarterly data for the period (2004Q1–2021Q4), converted using Eviews 12. To measure the objective of the study, the path analysis method was used using IBM SPSS-AMOS. The study concluded that the direct and indirect effects of financial variables have a weak role in directing bank credit towards the productive sectors in Iraq, which amounted to (0.18), as a result of market risks or unstable expectations in the economy. In addition to the weak credit ratings of borr

Architecture has evolved through the ages as forms, relationships, materials and mechanisms according to the data of each era and up to the era of digital technology, where the change in proportions and aesthetic dimensions of contemporary architectural formation due to the capabilities of digitization has created innovative plastic properties using the void formation in the facades and the introduction of void as a formative and aesthetic element, which led to The emergence of new creative concepts and ideas that contradict traditional ideas and are consistent with the spirit of the times, led to a revolution in the world of architectural form at the level of (architectural ideas and the generation of shapes, materials and construction

PvcABCD are cluster of genes found in Pseudomonas aeruginosa. The research was designed to examine the relationship between the pvc genes expression and cupB gene, which plays a crucial role in the development of biofilm, and rhlR, which regulates the expression of biofilm-related genes, and to investigate whether the pvc genes form one or two operons. The aims were achieved by employing qRT-PCR technique to measure the gene expression of genes of interest. It was found that out of 25 clinical isolates, 21 isolates were qualified as P.aeruginosa. Amongst, 18(85.7%) were evaluated as biofilm producers, 10 (47.6%), 5 (23.8%), and 3 (14.2%) were evaluated as strong, moderate and weak producers respectively, while, 3 (14.2%) were considered

ABSTRACT In dam construction stages when an earth embankment has retained a reservoir with constant water surface elevation for a long time, seepage conditions within the embankment will be reach a steady state. If it is necessary to drain the reservoir quickly, the pore-water pressures in the embankment may remain relatively high while the stabling effect of the reservoir's weight along the upstream (U/S) side for the embankment has removed. This process is referring to as "Rapid Drawdown" and may be cause instability in the upstream (U/S) face of the embankment. Kongele dam is one of the proposed earth dams to be implement within the current plan in Iraq. The authors study pore water pressure and the effect of rapid drawdown for the dam d

Monaural source separation is a challenging issue due to the fact that there is only a single channel available; however, there is an unlimited range of possible solutions. In this paper, a monaural source separation model based hybrid deep learning model, which consists of convolution neural network (CNN), dense neural network (DNN) and recurrent neural network (RNN), will be presented. A trial and error method will be used to optimize the number of layers in the proposed model. Moreover, the effects of the learning rate, optimization algorithms, and the number of epochs on the separation performance will be explored. Our model was evaluated using the MIR-1K dataset for singing voice separation. Moreover, the proposed approach achi

In present work the effort has been put in finding the most suitable color model for the application of information hiding in color images. We test the most commonly used color models; RGB, YIQ, YUV, YCbCr1 and YCbCr2. The same procedures of embedding, detection and evaluation were applied to find which color model is most appropriate for information hiding. The new in this work, we take into consideration the value of errors that generated during transformations among color models. The results show YUV and YIQ color models are the best for information hiding in color images.

Machine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a

Laser-Induced Breakdown Spectroscopy (LIBS) has been documented as an Atomic Emission Spectroscopy (AES) technique, utilising laser-induced plasma, in order to analyse elements in materials (gases, liquids and solid). The Nd:YAG laser passively Q-switched at 1064nm and 9ns pulse duration focused by convex lens with focal length 100 mm to generates power density 5.5×1012 Mw/mm2 with optical spectrum in the range 320-740 nm. Four soil samples were brought from different northern region of Iraq, northern region (Beiji, Sherkat, Serjnar and Zerkary).
The soil of the Northern region of Beige, Sherkat, Serjnar and Zarkary has abundant ratios of the elements P [0.08, 0.09, 0.18, 0.18] and Ca [0.61, 0.15, 0.92, 0.92] while it lack of Si [0.0

To perform a secure evaluation of Indoor Design data, the research introduces a Cyber-Neutrosophic Model, which utilizes AES-256 encryption, Role-Based Access Control, and real-time anomaly detection. It measures the percentage of unpredictability, insecurity, and variance present within model features. Also, it provides reliable data security. Similar features have been identified between the final results of the study, corresponding to the Cyber-Neutrosophic Model analysis, and the cybersecurity layer helped mitigate attacks. It is worth noting that Anomaly Detection successfully achieved response times of less than 2.5 seconds, demonstrating that the model can maintain its integrity while providing privacy. Using neutrosophic sim