For criminal investigations, fingerprints remain the most reliable form of personal identification despite developments in other fields like DNA profiling. The objective of this work is to compare the performance of both commercial charcoal and activated carbon powder derived from the Alhagi plant to reveal latent fingerprints from different non-porous surfaces (cardboard, plain glass, aluminum foil sheet, China Dish, Plastic, and Switch). The effect of three variables on activated carbon production was investigated. These variables were the impregnation ratio (the weight ratio of KOH: dried raw material), the activation temperature, and the activation time. The effect factors were investigated using Central Composite Design

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

Due to the lack of statistical researches in studying with existing (p) of Exogenous Input variables, and there contributed in time series phenomenon as a cause, yielding (q) of Output variables as a result in time series field, to form conceptual idea similar to the Classical Linear Regression that studies the relationship between dependent variable with explanatory variables. So highlight the importance of providing such research to a full analysis of this kind of phenomena important in consumer price inflation in Iraq. Were taken several variables influence and with a direct connection to the phenomenon and analyzed after treating the problem of outliers existence in the observations by (EM) approach, and expand the sample size (n=36) to

   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

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

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

the bank sect for any country  is very important  because  its represent a major  nerve   to feed a verity economic and finance activities .development any state measure by development  banking  sets and its represent  important  factor to investors attract . and because  important  of this subject ,teen accounting rule is a specialized for it .its related by  Disclosures in the Financial Statements Of Banks and The Similar Institutions, its accredit  by auditing and accounting standard  consul in republic of Iraq.in date 10/28/1998.                      &

Abstract

                  The research seeks to shed light on green accounting information systems, analyze them, identify sustainability reporting and how to improve it, as well as study the importance of the Iraqi oil sector, analyze it, and work on applying green accounting information systems in order to improve the quality of sustainability reporting. Oil as a branch of the General Corporation for the Distribution of Oil and Gas Products to apply the practical aspect and prove the hypothesis of the research. Explaining the company's role in improving environmental conditions

Objectives: The present study aims at detecting the depression among nurses who provide care for infected patients with corona virus phenomenon and to find out relationships between the depression and their demographic characteristics of age, gender, marital status, type of family, education, and years of experience of nurses in heath institutions, infection by corona virus, and their participation in training courses.
Methodology: A descriptive study is established for a period from October 10th, 2020 to April 15th, 2021. The study is conducted on a purposive (non-probability) sample of (100) nurse who are providing care for patients with COVID-19 and they are selected from the isolation wards. The instrument of the study is develope