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 Conventional audit techniques have become outdated due to factors such as the accuracy of d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 research seeks to find the relationship between psychological flow and futuristic thinking among postgraduate students. To this end, the researchers have made up two scales: one scale to measure the psychological flow which consisted of (32) items and the other to measure the futuristic thinking included (39) items which were distributed into three domains. As to collect the required data, the two scales had applied on a sample comprised (200) postgraduate students. The findings revealed that there is a correlation between psychological flow and futuristic thinking. The researcher recommended the coming studies take the relationship between psychological flow and psychological happiness.

A method has been demonstrated to synthesise effective zeolite membranes from existing crystals without a hydrothermal synthesis step.

Salinity of soil or irrigation water is one of the most important obstacle towards crop production and productivity, especially with the increasing scarcity of fresh water in Iraq and the Arab countries. The impact of salinity will be alleviated with the increasing temperature due to global warming. The objectives of this article was to shed some light on traits more related to salinity stress tolerance in oats, and to identify genetic variation of these traits. A split-plot arrangement experiment with RCBD was applied through 2011-2013 on the farm of Dept. of Field Crops/Coll. of Agric./Univ. of Baghdad. The oats cultivars; Hamel, Pimula and Genzania were set in sub-plots, whereas water quality was set in main-plots. Water quality had two

Elzaki Transform Adomian decomposition technique (ETADM), which an elegant combine, has been employed in this work to solve non-linear Riccati matrix differential equations. Solutions are presented to demonstrate the relevance of the current approach. With the use of figures, the results of the proposed strategy are displayed and evaluated. It is demonstrated that the suggested approach is effective, dependable, and simple to apply to a range of related scientific and technical problems.

Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le

Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le

The field of structural optimization (optimal design) has grown rapidly over the past decades with many different optimization methods that could be used to produce a structure of minimum weight. This research deals with two aspects, in the first, a general numerical technique based on the finite element analysis and it suggests to investigate the preliminary behavior of metal stiffened plate under action of static load environment. The technique was included a finite element model of the structures using high- order isoparimetric plate elements to be used to create a certain models to obtain their optimum design. The models are characterized such that, each model is builded using different types of stiffener configuration. The second as

The Hopfield network is one of the easiest types, and its architecture is such that each neuron in the network connects to the other, thus called a fully connected neural network. In addition, this type is considered auto-associative memory, because the network returns the pattern immediately upon recognition, this network has many limitations, including memory capacity, discrepancy, orthogonally between patterns, weight symmetry, and local minimum. This paper proposes a new strategy for designing Hopfield based on XOR operation; A new strategy is proposed to solve these limitations by suggesting a new algorithm in the Hopfield network design, this strategy will increase the performance of Hopfield by modifying the architecture of t