This study was conducted in a laboratory experiment at the University of Baghdad, College of Science, computing Department, 5 km from the center of Baghdad city, in 2021 to evaluate the sorting method for the tomato crop. The experiments were conducted in a factorial experiment under a complete randomized design with three replications and using SAS analysis, artificial neural network, image processing, the study of external characteristics, and physical features; fruit surface area and fruit circumference were 1334.46 cm2,57.53 cm2 and free diseases. The error value was less than zero, while training with outputs recorded the highest value and which was 5. The neural network's performance between the input and the mean square of th

This study aimed to evaluate the sustainable efficiency and calculate the sustainable value, opportunity cost and revenue to cost of potato production farms in Baghdad Governorate. Data were collected from a random sample of 102 spring potato producers in Baghdad governorate for the year 2022, the value-added function was estimated using three levels: economic (seeds and space), and social (education level), while environmental represented by (residual and volatile of nitrogen). Effective resources were calculated to extract the sustainability value- SV appeared on an average of 18023.15 thousand Iraqi dinars. Positive relationship with residual nitrogen and productivity, and Inverse relationship to the amount of volatile nitrogen.

This research came with the aim of showing the impact of governance mechanisms on tax avoidance practices, and in light of this, the financial data of the joint stock companies (industrial, service, agricultural, and hotels) listed in the Iraq Stock Exchange amounting to (35) companies were collected during the period (2009-2020). Through the financial reports published on the market website, multiple linear regression analysis was used as a tool to study the relationship between variables, and (Eviews 12) program was used for analysis and hypothesis testing. To achieve the objectives of the research,(administrative ownership, board size, board independence, women's membership) was adopted as an indicator of the dimensions of governance, an

Biometrics represent the most practical method for swiftly and reliably verifying and identifying individuals based on their unique biological traits. This study addresses the increasing demand for dependable biometric identification systems by introducing an efficient approach to automatically recognize ear patterns using Convolutional Neural Networks (CNNs). Despite the widespread adoption of facial recognition technologies, the distinct features and consistency inherent in ear patterns provide a compelling alternative for biometric applications. Employing CNNs in our research automates the identification process, enhancing accuracy and adaptability across various ear shapes and orientations. The ear, being visible and easily captured in

The use of appropriate and accurate language is of utmost importance when describing people on the move and their dilemma, particularly refugees and displaced persons who have unique legal protection. So, there are a lot of scholars who have investigated the United Nations High Commissioner for Refugees’ (UNHCR) reports, but no one has examined representational and interactional meanings of UNHCR reports. Accordingly, this research aims to explore the role of UNHCR reports in enhancing the value of the humanitarian, which is attributed to the uniqueness of its use of language. The current study investigates the manner in which the textual content interacts with the images that are associated with the category of the UNHCR reports. Four re

Facial emotion recognition finds many real applications in the daily life like human robot interaction, eLearning, healthcare, customer services etc. The task of facial emotion recognition is not easy due to the difficulty in determining the effective feature set that can recognize the emotion conveyed within the facial expression accurately. Graph mining techniques are exploited in this paper to solve facial emotion recognition problem. After determining positions of facial landmarks in face region, twelve different graphs are constructed using four facial components to serve as a source for sub-graphs mining stage using gSpan algorithm. In each group, the discriminative set of sub-graphs are selected and fed to Deep Belief Network (DBN) f