Small and Medium Enterprises (SMEs) in Iraq have experienced low performance due to the limited usage of accounting information systems (AIS) and the inability to exploit knowledge of management capabilities (KMC). These deficiencies have led to competitive pressures in the marketplace that have adversely affected their sales and production. This study investigates the role of AIS in terms of operation support, knowledge support, regulatory support, and the role of KMC, including knowledge acquisition, knowledge transfer, and knowledge utilized to enhance organizational performance in Iraqi SMEs. The target population was managers and owners in SMEs using AIS in Iraq’s cities. A non-probability purposive sampling technique was use

Background Cadmium (Cd), one of the most abundant heavy metals, is extremely toxic to both humans and animals. hIt is well known that zinc (Zn) administration reduces Cd-induced toxicity and that metallothioneins can have a protective effect in biological systems to mitigate Cd toxicity. Objective The aim of the current study to determine if Zn administration affected the induction of MT-1 and MT-2 in the liver tissue in mice exposed to Cd. Materials and methods Metallothionein protein (MT) level in the tissue of male mice were detected using the anion -exchang high-performance liquid chromatography coupled (HPLC)assay and immunohistochemical staining. Results Single treatment to zinc or cadmium increase the level of MT in the liver, but zi

Use Almtafr axis to study the response component that isolates gave a positive response to the use of standard Almtafr which leads to lower the temperature and the number of cells at a temperature suitable Rifampicin resistant less than that TJ and similarly reflected on the frequency of mutations induced

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

Background: The efficacy of educational strategies is crucial for nursing students to competently perform pediatric procedures like nasogastric tube insertion. Specific Background: This study evaluates the effectiveness of simulation, blended, and self-directed learning strategies in enhancing these skills among nursing students. Knowledge Gap: Previous research lacks a comprehensive comparison of these strategies' impacts on skill development in pediatric nursing contexts. Aims: The study aims to assess the effectiveness of different educational strategies on nursing students' ability to perform pediatric nasogastric tube insertions. Methods: A pre-experimental design was employed at the College of Nursing, University of Baghdad, i

HM Al-Dabbas, RA Azeez, AE Ali, Iraqi Journal of Science, 2023

The proliferation of many editing programs based on artificial intelligence techniques has contributed to the emergence of deepfake technology. Deepfakes are committed to fabricating and falsifying facts by making a person do actions or say words that he never did or said. So that developing an algorithm for deepfakes detection is very important to discriminate real from fake media. Convolutional neural networks (CNNs) are among the most complex classifiers, but choosing the nature of the data fed to these networks is extremely important. For this reason, we capture fine texture details of input data frames using 16 Gabor filters indifferent directions and then feed them to a binary CNN classifier instead of using the red-green-blue