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

The researchers in this study, which aimed to find out Degree contribution of Iraqi
women in development from the perspective faculty members of the complex Jadriya
University in Baghdad, and the the impact of demographic variables (gender, college, place of
living, school level,) for its contribution.
The study population consisted of some faculty members Jadiriyah compound in
Baghdad's University for the academic year 20012/2013. This study followed a descriptive
approach the field, and the analytical method, the study sample consisted of (250) teaching all
of College of Science for girls and education for girls, and to achieve objective of the study
was the development of a questionnaire, was sure of its sincer

The study aimed to identify the reality of the application of the organizational equity empowerment at the Jordanian government institutions from the viewpoint of women employees in terms of each of the (delegation equity, training equity, appraisal equity, join in committees equity, participation in decision-making equity), and the impact of non-application of equity empowerment on performance.

Population of the study amounted (986) women employee, while the researcher distributed (340) questionnaire through a randomly sample method.

The study used the questionnaire as a tool to collect the data. And to ensure the reliability of the questionnaire has been calculated Cronbach's co

Trichomonas vaginalis is a causative agent of trichomoniasis , one of the most common non-viral sexually transmitted disease (STD) over all the world, especially in immunocompromised women such as pregnant. Wet smear and Giemsa stain are the current methods used in hospital to diagnosis trichomoniasis. DNA based diagnosis is still to be validated to diagnose the local isolates, the objective of the present study was to compare the conventional methods of disease diagnosis with the DNA-based method to diagnose Trichomonas incidence in local isolates. In the present study, 105 samples were collected from outpatient women (18-45 years) of Maternity hospital in Mosul who showed a classical presentation of Trichomonas

In addition to their high quantities of active chemicals, medicinal plants are well-known for their pharmacological qualities, which include immunological modulation. T Consequently, this study aimed to examine the effects of Avena sativa and Glycyrrhiza glabra leaf extracts on immunological responses as measured by blood cytokine and liver enzyme levels. The phytochemical analysis of Avena sativa crude leaf extracts revealed the presence of alkaloids,flavonoids, tannins, phenolic compounds, and saponins but the absence of resins and violet oils. On the other hand, violet oils, flavonoids, tannins, saponins, and glycosides were detected in significant concentration in Glycyrrhiza glabra ethanolic extract, although resins and phenolic compou

Heart sound is an electric signal affected by some factors during the signal's recording process, which adds unwanted information to the signal. Recently, many studies have been interested in noise removal and signal recovery problems. The first step in signal processing is noise removal; many filters are used and proposed for treating this problem. Here, the Hankel matrix is implemented from a given signal and tries to clean the signal by overcoming unwanted information from the Hankel matrix. The first step is detecting unwanted information by defining a binary operator. This operator is defined under some threshold. The unwanted information replaces by zero, and the wanted information keeping in the estimated matrix. The resulting matrix

Anomaly detection is still a difficult task. To address this problem, we propose to strengthen DBSCAN algorithm for the data by converting all data to the graph concept frame (CFG). As is well known that the work DBSCAN method used to compile the data set belong to the same species in a while it will be considered in the external behavior of the cluster as a noise or anomalies. It can detect anomalies by DBSCAN algorithm can detect abnormal points that are far from certain set threshold (extremism). However, the abnormalities are not those cases, abnormal and unusual or far from a specific group, There is a type of data that is do not happen repeatedly, but are considered abnormal for the group of known. The analysis showed DBSCAN using the