Iraqi Journal for Computers and Informatics <p>Iraqi Journal for Computers and Informatics is an open access ,double-blind peer reviewed, international academic journal published biannual (since 2017). It is institutional journal issued by the University of Information Technology and Communications (UoITC) in Baghdad- Iraq; UoITC is one of governmental universities which established by the Ministry of Higher Education in Iraq. IJCI aims to contribute to the constant scientific research and to provide a sober scientific journal that enriches scholars around the world and it deals with all aspects of computer science.</p> en-US <p>IJCI applies the Creative Commons Attribution (CC BY) license to articles. The author of the submitted paper for publication by IJCI has the CC BY license. Under this Open Access license, the author give an agreement to any author to reuse the article in whole or part for any purpose, even for commercial purposes. Anyone may copy, distribute, or reuse the content as long as the author and original source are properly cited. This facility helps in re-use and ensures that journal content is available for the needs of research.&nbsp;<br>If the manuscript contains photos, images, figures, tables, audio files, videos, etc., that the author or the co-authors do not own, IJCI will require author to provide the journal with proof that the owner of that content has given the author written permission to use it, and the owner has approved that the CC BY license being applied to content. IJCI provides a form that author can use to ask for permission from the owner. If the author does not have owner permission, IJCI will ask author to remove that content and/or replace it with other content that the author own or have such permission to use.&nbsp;<br>Many authors assume that if they previously published a paper through another publisher, they have the rights to reuse that content in their PLOS paper, but that is not necessarily the case – it depends on the license that covers the other paper. Author must ascertain the rights he/she has of a specific license (a license that enables author to use the content). Author must obtain a written permission from the publisher to use the content in IJCI paper. Author should not include any content in her/his IJCI paper without having the rights to use, and always give proper attribution.&nbsp;<br>The accompanying submitted data should be stated with licensing policies, the policies should not be more restrictive than CC BY.&nbsp;<br>IJCI has the right to remove photos, captures, images, figures, tables, illustrations, audio and video files, from a paper before or after publication, if these contents were included in author paper without permission from the owner of the content.&nbsp;</p> (Prof. Dr. Safaa O. Al-mamory) (Ahmed Jasim) Sat, 02 Apr 2022 21:39:25 +0300 OJS 60 SURVEY: AUDIO READING SYSTEM FOR BLIND PERSONS <p>Audio Reading System is used to help blind people to read the text based on camera as input device and speaker as output device. The system used the OCR algorithm to extract the text from input image and Text-to-Speech algorithm to convert text into corresponding voice. In this paper, we review newest research of audio reading system. We discuss the hardware and software, which is used, on system for different types approach. Finally, the result of this paper that is: Raspberry pi, python and tesseract are best tools used in Audio reading system. Also the braille and finger print devices are not efficient and not easy to use.</p> Mohammed Ali Mohammed, Karim Q. Hussein, Mustafa Dhiaa Al-Hassani Copyright (c) 2022 Sat, 02 Apr 2022 00:00:00 +0300 IMPROVING THE PRIORITIZATION PROCEDURE OF PATIENTS WITH COVID-19 IN HOSPITALS BASED ON DECISION-MAKING TECHNIQUES: A SYSTEMATIC REVIEW <p>Coronavirus-specific antibodies can be detected in the blood of people who have recently recovered from coronavirus disease-2019 (COVID-19). Convalescent-Plasma (CP) transfusion process proved that it's among the most efficient protocols, and it's used in hospitals to treat various infections and diseases. Several medical issues have been addressed due to the growing interest in creating Artificial Intelligence (AI) applications. However, considering the virus's enormous potential harm to global public health, such uses are insufficient. This proposed systematic review and meta-analysis aims to obtain an overview of COVID-19, highlight the limits of decision-making approaches, and give healthcare professionals information about the technique's advantages. Between 2016 and 2021, five databases, namely IEEE Xplore, Web of Science, PubMed, Science Direct, and Scopus, were utilized to run four sequences of search queries. As a result, 477 studies are found to be relevant. Only six studies were thoroughly examined and included in this review after screening articles and using proper inclusion criteria, highlighting the lack of research on this crucial topic. Studies' findings were reviewed to identify the gaps in all the evaluated papers. Motivations, problems, constraints, suggestions, and case examples were thoroughly examined. This study seeks to answer how we support the researchers with collected information for managing transfusion of the highest quality CP to the most critical COVID-19 patients across telemedicine hospitals.</p> Thura J. Mohammed, Suha M. Hadi, A. S. Albahri Copyright (c) 2022 Thu, 05 May 2022 00:00:00 +0300 Review of Detection Denial of Service Attacks using Machine Learning through Ensemble Learning <p>Today's network hacking is more resource-intensive because the goal is to prohibit the user from using the network's resources when the target is either offensive or for financial gain, especially in businesses and organizations. That relies on the Internet like Amazon Due to this, several techniques, such as artificial intelligence algorithms like machine learning (ML) and deep learning (DL), have been developed to identify intrusion and network infiltration and discriminate between legitimate and unauthorized users. Application of machine learning and ensemble learning algorithms to various datasets, consideration of homogeneous ensembles using a single algorithm type or heterogeneous ensembles using several algorithm types, and evaluation of the discovery outcomes in terms of accuracy or discovery error for detecting attacks. The survey literature provides an overview of the many approaches and approaches of one or more machine-learning algorithms used in various datasets to identify denial of service attacks. It has also been shown that employing the hybrid approach is the most common and produces better attack detection outcomes than using the sole approaches. Numerous machine learning techniques, including support vector machines (SVM), K-Nearest Neighbors (KNN), and ensemble learning like random forest (RF), bagging, and boosting, are illustrated in this work (DT). That is employed in several articles to identify different denial of service (DoS) assaults, including the trojan horse, teardrop, land, smurf, flooding, and worm. That attacks network traffic and resources to deny users access to the resources or to steal confidential information from the company without damaging the system and employs several algorithms to obtain high attack detection accuracy and low false alarm rates.</p> Nazanin Najm Abdulla, Rajaa K. Hasoun Copyright (c) 2022 Thu, 30 Jun 2022 00:00:00 +0300