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

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

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

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

With the growth of mobile phones, short message service (SMS) became an essential text communication service. However, the low cost and ease use of SMS led to an increase in SMS Spam. In this paper, the characteristics of SMS spam has studied and a set of features has introduced to get rid of SMS spam. In addition, the problem of SMS spam detection was addressed as a clustering analysis that requires a metaheuristic algorithm to find the clustering structures. Three differential evolution variants viz DE/rand/1, jDE/rand/1, jDE/best/1, are adopted for solving the SMS spam problem. Experimental results illustrate that the jDE/best/1 produces best results over other variants in terms of accuracy, false-positive rate and false-negative

Pigeons have accompanied humans since ancient time because they are used as a source of food, pets, hobby, and religious symbols. Pigeons have shown high prevalence rate of infection with gastrointestinal helminths and protozoan. This study was conducted to evaluate the prevalence of parasitic infections in the domestic pigeon (Columba livia domestica) from October, 2017 to April, 2018, purchased from bird market of Zakho City, Kurdistan region. The samples were taken from 50 adult pigeons (28 males and 22 females). The birds were transferred to Parasitology Laboratory, Faculty of Science, Zakho University. In the laboratory, each bird was sacrificed and immediately the feather and skin of under wings, chest and the rest of the

The main objective of the central bank is to achieve price stability and target in fractionates. Therefore, the bank sought to use modern tools and policies in order to reduce the negative effects of the accumulation of foreign reserves represented by monetary sterilization, similar to developed and developing countries alike, but with different available tools that are possible and imposed by the local financial and monetary environments, such as the window for buying and selling foreign currency, open market operations and deposit facilities. And lending existing. Because any in crease in the monetary base resulting from the accumulation of foreign reserves will affect price stability directly due to the consumer nature of the

The dividends is one of difficult and important decisions taken by the administration in the economic units, because this decision has a direct impact on the investor and economic unit, so the main objective of any investor is achieve earnings, as well as information borne by dividends about the earnings quality of the economic unit and the level and efficiency of management to achieving earnings.

The research aims at explaining the effect of the dividends policy on the earnings quality in the companies listed in the Iraq Stock Exchange. The Miller model was used to measu