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

Bacteriocin is an important antimicrobial peptide that can be used in industrial and medical fields due to its characteristics of antibacterial, food preservation and anticancer activities. Fifty isolates of Bacillus sp were collected from different soil samples which were already recognized via morphological and biochemical identification process. The isolates were screened for bacteriocin production effective against Staphylococcus spp in order to select the highest producing isolate. The isolate NK16 showed the maximum bacteriocin production (80 AU/ml) which was further characterized as Bacillus subtilis NK 16 through using API identification system (API 20E and API 50CHB). Then, next step was to detect the optimal conditions for maximum

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

     Community detection is an important and interesting topic for better understanding and analyzing complex network structures. Detecting hidden partitions in complex networks is proven to be an NP-hard problem that may not be accurately resolved using traditional methods. So it is solved using evolutionary computation methods and modeled in the literature as an optimization problem.  In recent years, many researchers have directed their research efforts toward addressing the problem of community structure detection by developing different algorithms and making use of single-objective optimization methods. In this study, we have continued that research line by improving the Particle Swarm Optimization (PSO) algorithm using a

     Community detection is an important and interesting topic for better understanding and analyzing complex network structures. Detecting hidden partitions in complex networks is proven to be an NP-hard problem that may not be accurately resolved using traditional methods. So it is solved using evolutionary computation methods and modeled in the literature as an optimization problem.  In recent years, many researchers have directed their research efforts toward addressing the problem of community structure detection by developing different algorithms and making use of single-objective optimization methods. In this study, we have continued that research line by improving the Particle Swarm Optimization (PSO) algorithm using a local

This research deals with processing and Interpretation of Bouguer anomaly gravity field, using two dimensional filtering techniques to separate the residual gravity field from the Bouguer gravity map for a part of Najaf Ashraf province in Iraq. The residual anomaly processed in order to reduce noise and give a more comprehensive vision about subsurface linear structures. Results for descriptive interpretation presented as colored surfaces and contour maps in order to locate directions and extensions of linear features which may interpret as faults. A comparison among gravity residual field , 1st derivative and horizontal gradient made along a profile across the study area in order to assign the exact location of a major fault. Furthermor