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

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

This study detects the presence of cholesterol in an Iraqi plant named Suaeda baccata Forsk of the family Chenopodiacae, wildly and widely grown in Iraq. The absence of any publication concerning the sterol content of this Suaeda specie, and the industrial importance of cholesterol depending on its role as a precursor in the synthesis of some hormones, like progesterone, acquired this study its value. The investigations revealed the presence of cholesterol that was proved by TLC together with the standard compound cholesterol, and anisaldehyde spray reagent using three different solvent systems, then authenticated by HPLC, in which the reten

The Present investigation includes the isolation and identification of Pseudomonas aeruginosa for different cases of hospital contamination from 1/ 6/2003 to 30/9/2004, the identification of bacteria depended on morphological , cultural and biochemical characters, 37 of isolates were diagnosed from 70 smears from wounds and burns beside 25 isolates were identified from 200 smears taken from operation theater and hospital wards including the floors , walls , sources of light and operation equipment the sensitivity of all isolates to antibiotic were done , which exhibited complete sensitivity to Ciprofloxacin , Ceftraixon, Tobromycin and Gentamysin ,while they were complete resist to Amoxcillin , Tetracyclin , Nitrofurantion , Clindamycin C

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

Background: White spot lesions are esthetic problems caused by subsurface enamel demineralization that seen as white opacity. Aim of the study: This study aimed to evaluate and to compare the color change after the treatment of the white spot lesions with resin ‹nϔ‹Žtrƒt‹on and micro abrasion. Materials and Methods: rt‹ϔ‹…‹ƒŽ white spot lesions were generated on 48 premolar teeth by the use of a demineralization solution. The teeth were randomly divided using the Diagnodent into three study groups (16 teeth for each group) depending on the depth of the induced lesions: outer enamel, inner enamel and outer dentine. Then each group was fatherly subdivided into two groups (8 teeth for each group) the ϔ‹rst group was treated wit

The process of identifying the region is not an easy process when compared with other operations within the attribute or similarity. It is also not difficult if the process of identifying the region is based on the standard and standard indicators in its calculation. The latter requires the availability of numerical and relative data for the data of each case Any indicator or measure is included in the legal process

In this work, ZnO quantum dots (Q.dots) and nanorods were prepared. ZnO quantum dots were prepared by self-assembly method of zinc acetate solution with KOH solution, while ZnO nanorods were prepared by hydrothermal method of zinc nitrate hexahydrate Zn (NO3)2.6H2O with hexamethy lenetetramin (HMT) C6H12N4. The optical , structural and spectroscopic properties of the product quantum dot were studied. The results show the dependence of the optical properties on the crystal dimension and the formation of the trap states in the energy band gap. The deep levels emission was studied for n-ZnO and p-ZnO. The preparation ZnO nanorods show semiconductor behavior of p-type, which is a difficult process by doping because native defects.