The current study aims to identify:The meta-motivation and Uniqueness seeking of the study sample. The correlated  relationship among them. The present study sample consists of (400) students from the colleges of engineering, University of Baghdad, and the University of Technology in the academic year (2019-2020), and the researcher has adopted the Chen Scale (1995)to measure the meta-motivation after its translation into Arabic by(Al-Samawi,2011).The scale includes six dimensions. The researcher has also adopted the Snyder&Fromkin scale (1980) to measure the uniqueness  seeking after translating and adapting it into the Arabic environment. The scale consists of three dimensions. The results show that students of the Facult

 Urban agriculture is one of the important urban uses of land in cities since the inception of cities and civilizations, but the great expansion of cities in the world during the twentieth century and the beginning of the twentieth century and the increase in the number of urban residents compared to the rural population has led to a decline in this use in favor of other uses.

 This decline in agricultural and green land areas in cities has negatively affected the environment, natural life and biological diversity in cities in addition to the great impact on the climate and the increase in temperatures and the negative impact on the economic side, since urban agriculture is an important pillar of the economy, especially

The monitoring weld quality is increasingly important because great financial savings are possible because of it, and this especially happens in manufacturing where defective welds lead to losses in production and necessitate time consuming and expensive repair. This research deals with the monitoring and controllability of the fusion arc welding process using Artificial Neural Network (ANN) model. The effect of weld parameters on the weld quality was studied by implementing the experimental results obtained from welding a non-Galvanized steel plate ASTM BN 1323 of 6 mm thickness in different weld parameters (current, voltage, and travel speed) monitored by electronic systems that are followed by destructive (Tensile and Bending) and non

This research deals with the case of the Iraqi joint-stock companies listed on the Iraq Stock Exchange study in terms of compliance with the requirements of IAS 33 "Earnings per share" and the research problem Alrtash concentrated in a statement the commitment of those companies the requirements of the International Standard 33, which may adversely affect the quality of financial reporting where and in particular the quality of accounting information and content of the primary and secondary characteristics make them be of interest to the decisions of its users, so the aim of this research to the statement of financial reporting earnings per share on the quality of financial reporting in listed shareholding in Iraq Stock Exchange

   Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct

     أجري البحث لمعرفة الملوثات الميكروبية الموجودة على قشرة وفي صفار وبياض بيض الدجاج المحلي ، السوري ، التركي ، الاوكراني ، حيث جمعت العينات بمعدل 10 بيضة من الاسواق الشعبية في محافظة  بغداد . أظهرت النتائج أن بكتريا السالمونيلا واضحة في صفار البيض التركي .  وفي قشرة وبياض وصفار البيض الاوكراني . كما أظهرت نتائج فحص البيض

Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

Objective(s): To assess the eating habits of adolescent females with iron deficient anemia.

Methodology: This study employed a quantitative research, descriptive evaluation design.The study was carried out on adolescent girls attending Kirkuk secondary school, period from 11 April to 27 December 2022. A non- probability (Purposive) sample has been applied to obtain the study goals. The study sample was (62) student who participate in the study.

Results: Pre-test results from the study revealed that 54.8% of students had moderate IDA. While the students' iron levels returned to normal in the posttest (53.2%). The majority of students (59.7%) had poor eatin

A medical- service platform is a mobile application through which patients are provided with doctor’s diagnoses based on information gleaned from medical images. The content of these diagnostic results must not be illegitimately altered during transmission and must be returned to the correct patient. In this paper, we present a solution to these problems using blind, reversible, and fragile watermarking based on authentication of the host image. In our proposed algorithm, the binary version of the Bose_Chaudhuri_Hocquengham (BCH) code for patient medical report (PMR) and binary patient medical image (PMI) after fuzzy exclusive or (F-XoR) are used to produce the patient's unique mark using secret sharing schema (SSS). The patient’s un

This study included isolation and characterization of extremely halophilic bacteria from Al-Massab Al-Aam region in South of Iraq Fifty isolates were identified by using numerical taxonomy 40 strains belonged to the genus Halobacterium which inclucted Hb. halobium Hb. cutirubrum Hb. salinarium Hb. saccharovorum Hb. valismortis and Hb. volcanii. Ten strains belonged to the genus Halococcus which included Hc. morrhuae Hc. saccharolyticus. Growth curves were sensitive mutants determined for wild type and salt Generation time in logarthmic phase was measured and found to be (10.37 2hr 7 0.59) for Hb. salinarium / 18 (6.490 hr 0.24) for Hb. cutirubrum / 32, (6.700 hr + 0.488) for Hb. valismortis / 20, (11.243 hr + 0.96) for Hb. volcanii / 7. (7