This study aims to demonstrate the role of artificial intelligence and metaverse techniques, mainly logistical Regression, in reducing earnings management in Iraqi private banks. Synthetic intelligence approaches have shown the capability to detect irregularities in financial statements and mitigate the practice of earnings management. In contrast, many privately owned banks in Iraq historically relied on manual processes involving pen and paper for recording and posting financial information in their accounting records. However, the banking sector in Iraq has undergone technological advancements, leading to the Automation of most banking operations. Conventional audit techniques have become outdated due to factors such as the accuracy of d

The main purpose of the paper is to identify the controllability of an existing production system; yogurt production line in Abu Ghraib Dairy Factory which has several machines of food processing and packing that has been studied. Through the starting of analysis, instability in production has been found in the factory. The analysis is built depending on experimental observation and data collection for different processing time of the machines, and statistical analysis has been conducted to model the production system. Arena Software is applied for simulating and analyzing the current state of the production system, and results are expanded to improve the system production and efficiency. Research method is applied to contribute in knowi

A steganography hides information within other information, such as file, message, picture, or video. A cryptography is the science of converting the information from a readable form to an unreadable form for unauthorized person. The main problem in the stenographic system is embedding in cover-data without providing information that would facilitate its removal. In this research, a method for embedding data into images is suggested which employs least significant bit Steganography (LSB) and ciphering (RSA algorithm) to protect the data. System security will be enhanced by this collaboration between steganography and cryptography.

<span>One of the main difficulties facing the certified documents documentary archiving system is checking the stamps system, but, that stamps may be contains complex background and surrounded by unwanted data. Therefore, the main objective of this paper is to isolate background and to remove noise that may be surrounded stamp. Our proposed method comprises of four phases, firstly, we apply k-means algorithm for clustering stamp image into a number of clusters and merged them using ISODATA algorithm. Secondly, we compute mean and standard deviation for each remaining cluster to isolate background cluster from stamp cluster. Thirdly, a region growing algorithm is applied to segment the image and then choosing the connected regi

<p class="0abstract">Image denoising is a technique for removing unwanted signals called the noise, which coupling with the original signal when transmitting them; to remove the noise from the original signal, many denoising methods are used. In this paper, the Multiwavelet Transform (MWT) is used to denoise the corrupted image by Choosing the HH coefficient for processing based on two different filters Tri-State Median filter and Switching Median filter. With each filter, various rules are used, such as Normal Shrink, Sure Shrink, Visu Shrink, and Bivariate Shrink. The proposed algorithm is applied Salt&amp; pepper noise with different levels for grayscale test images. The quality of the denoised image is evaluated by usi

ZnS nanoparticles were prepared by a simple microwave irradiation method under mild condition. The starting materials for the synthesis of ZnS quantum dots were zinc acetate (R & M Chemical) as zinc source, thioacetamide as a sulfur source and ethylene glycol as a solvent. All chemicals were analytical grade products and used without further purification. The quantum dots of ZnS with cubic structure were characterized by X-ray powder diffraction (XRD), the morphology of the film is seen by scanning electron microscopy (SEM). The particle size is determined by field effect scanning electron microscopy (FESEM), UV-Visible absorption spectroscopy and XRD. UV-Visible absorption spectroscopy analysis shows that the absorption peak of the as-prep