Several Intrusion Detection Systems (IDS) have been proposed in the current decade. Most datasets which associate with intrusion detection dataset suffer from an imbalance class problem. This problem limits the performance of classifier for minority classes. This paper has presented a novel class imbalance processing technology for large scale multiclass dataset, referred to as BMCD. Our algorithm is based on adapting the Synthetic Minority Over-Sampling Technique (SMOTE) with multiclass dataset to improve the detection rate of minority classes while ensuring efficiency. In this work we have been combined five individual CICIDS2017 dataset to create one multiclass dataset which contains several types of attacks. To prove the eff

Deepfake is a type of artificial intelligence used to create convincing images, audio, and video hoaxes and it concerns celebrities and everyone because they are easy to manufacture. Deepfake are hard to recognize by people and current approaches, especially high-quality ones. As a defense against Deepfake techniques, various methods to detect Deepfake in images have been suggested. Most of them had limitations, like only working with one face in an image. The face has to be facing forward, with both eyes and the mouth open, depending on what part of the face they worked on. Other than that, a few focus on the impact of pre-processing steps on the detection accuracy of the models. This paper introduces a framework design focused on this asp

Determining the face of wearing a mask from not wearing a mask from visual data such as video and still, images have been a fascinating research topic in recent decades due to the spread of the Corona pandemic, which has changed the features of the entire world and forced people to wear a mask as a way to prevent the pandemic that has calmed the entire world, and it has played an important role. Intelligent development based on artificial intelligence and computers has a very important role in the issue of safety from the pandemic, as the Topic of face recognition and identifying people who wear the mask or not in the introduction and deep education was the most prominent in this topic. Using deep learning techniques and the YOLO (”You on

Significant advances in the automated glaucoma detection techniques have been made through the employment of the Machine Learning (ML) and Deep Learning (DL) methods, an overview of which will be provided in this paper. What sets the current literature review apart is its exclusive focus on the aforementioned techniques for glaucoma detection using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines for filtering the selected papers. To achieve this, an advanced search was conducted in the Scopus database, specifically looking for research papers published in 2023, with the keywords "glaucoma detection", "machine learning", and "deep learning". Among the multiple found papers, the ones focusing

This study focuses on the relative frequency of Streptococcus pneumoniae in children with culture-proven bacterial meningitis. The epidemiology has been investigated with clinical and laboratory findings in The Central Public Health Laboratory, Iraq from April to September, 2010. From (138) samples , (55) cases (39.85 %) were diagnosed by physician as bacterial meningitis, (23) cases (16.66 %) as viral menginitis , (18) cases (13.04 %) as different medical cases (e.g febrile convulsion , meningoencephalitis , epilepsy …etc) and (42) cases (30.43 %) as unidentified medical cases. For bacterial meningitis S.pneumoniae was isolated from (10) cases (18.18 %) only. The median age for bacterial meningitis was (130.75) month and the predomina

This study presents a comprehensive list of the freshwater and marine bivalves distributed in Iraq. A total of 51 species were recorded, and distributed as: 14 freshwater species, and 37 marine species, these species belonging to 25 families, all available remarks on the distribution, taxonomy, and nomenclature of these species were given. This study included the recently collected specimens along with those previously studied and recorded in Iraq.

Many studies have focused on identifying and classifying freshwater fishes in Iraq, concerned with describing, organizing, and drawing up a list of freshwater fishes in Iraq or the Tigris and Euphrates rivers. Within the most recent updates at the beginning of 2023, 53 native freshwater and 20 exotic (alien or introduced) fish species are recorded and described. This study reviewed the database of morphology and molecular studies of freshwater fish in Iraq and reported species while surveying the fish fauna at different water bodies of the country from 2010 to the beginning of 2023. In conclusion, 29 species (about 40.3%) of all 72 fish species in Iraq still need to be available information on their molecular data.

During the syrvey on natural enemies of whiteflies in Iraq, the following. predators were recorded.