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 Conventional audit techniques have become outdated due to factors such as the accuracy of d

This research aims to deal with contemporary knowledge  methodology to correlate between operations strategy and technological change or modernization in productive paths for industrial organizations depend on practical indicators for competitive  priorities that is objectives of operations performance.

The research is based on main hypothesis, concentrates on determination of technological change which is decided by the level of technology deterioration in current operations path compared with the competitors leaders-technology leaders.

We apply these concepts on hypothetical case to two similar companies in their production nature and te

The study of determing Uranium concentration in samples of teeth is the first of its kind in the Iraq . In this study Uranium concentration has been measured was (32) samples of child teeth distributed on the some of middle and south governorate of Iraq (Muthana – Dekar – Basrah – Najaf – Karbalah – Waset – Babel – Baghdad) . The Uranium concentration in teeth samples has been measured by using fission tracks registration in (CR-39) track detector that caused by the bombardment of (U235) with thermal neutrons falx from (24Am.Be) neutron source that has flux of (5x103n.cm-2S-1). The result obtained show that the Uranium concentrations in governorates were (0.18ppm), (0.172ppm), (0.160ppm), 0.150ppm) (0.89ppm), (0.07ppm) , (0.

    Specimens of the sesarmid crab Nanonsesarma sarii  (Naderloo and Türkay 2009) were    collected from the intertidal zone of Khor Al-Zubair, Basrah, Iraq 2012 far from the Arabian Gulf coasts. Morphological features of this species are highlighted and a figure is provided. 

        Most vegetation’s are Land cover (LC) for the globe, and there is an increased attention to plants since they represent an element of balance to natural ecology and maintain the natural balance of rapid changes due to systematic and random human uses, including the subject of the current study (Bassia eriophora ) Which represent an essential part of the United Nations system for land cover classification (LCCS), developed by the World Food Organization (FAO) and the world Organization for environmental program (UNEP), to observe basic environmental elements with modern techniques. Although this plant is distributed all over Iraq, we found that this plant exists primarily in the middle

The segmentation of aerial images using different clustering techniques offers valuable insights into interpreting and analyzing such images. By partitioning the images into meaningful regions, clustering techniques help identify and differentiate various objects and areas of interest, facilitating various applications, including urban planning, environmental monitoring, and disaster management. This paper aims to segment color aerial images to provide a means of organizing and understanding the visual information contained within the image for various applications and research purposes. It is also important to look into and compare the basic workings of three popular clustering algorithms: K-Medoids, Fuzzy C-Mean (FCM), and Gaussia

Accurate emotion categorization is an important and challenging task in computer vision and image processing fields. Facial emotion recognition system implies three important stages: Prep-processing and face area allocation, feature extraction and classification. In this study a new system based on geometric features (distances and angles) set derived from the basic facial components such as eyes, eyebrows and mouth using analytical geometry calculations. For classification stage feed forward neural network classifier is used. For evaluation purpose the Standard database "JAFFE" have been used as test material; it holds face samples for seven basic emotions. The results of conducted tests indicate that the use of suggested distances, angles

In recent years, with the rapid development of the current classification system in digital content identification, automatic classification of images has become the most challenging task in the field of computer vision. As can be seen, vision is quite challenging for a system to automatically understand and analyze images, as compared to the vision of humans. Some research papers have been done to address the issue in the low-level current classification system, but the output was restricted only to basic image features. However, similarly, the approaches fail to accurately classify images. For the results expected in this field, such as computer vision, this study proposes a deep learning approach that utilizes a deep learning algorithm.