Cyberbullying is one of the biggest electronic problems that takes multiple forms of harassment using various social media. Currently, this phenomenon has become very common and is increasing, especially for young people and adolescents. Negative comments have a significant and dangerous impact on society in general and on adolescents in particular. Therefore, one of the most successful prevention methods is to detect and block harmful messages and comments. In this research, negative Arabic comments that refer to cyberbullying will be detected using a support vector machine algorithm. The term frequency-inverse document frequency vectorizer and the count vectorizer methods were used for feature extraction, and the results wer

The COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system

Machine Learning (ML) algorithms are increasingly being utilized in the medical field to manage and diagnose diseases, leading to improved patient treatment and disease management. Several recent studies have found that Covid-19 patients have a higher incidence of blood clots, and understanding the pathological pathways that lead to blood clot formation (thrombogenesis) is critical. Current methods of reporting thrombogenesis-related fluid dynamic metrics for patient-specific anatomies are based on computational fluid dynamics (CFD) analysis, which can take weeks to months for a single patient. In this paper, we propose a ML-based method for rapid thrombogenesis prediction in the carotid artery of Covid-19 patients. Our proposed system aims

     Lately, a growing interest has been emerging in age estimation from face images because of the wide range of potential implementations in law enforcement, security control, and human computer interactions. Nevertheless, in spite of the advances in age estimation, it is still a challenging issue. This is due to the fact that face aging process is not only set by distinct elements, such as genetic factors, but by extrinsic factors, such as lifestyle, expressions, and environment as well. This paper applied machine learning technique to intelligent age estimation from facial images using J48 classifier on FG_NET dataset. The proposed work consists of three phases; the first phase is image preprocessing which include

Abstract: A novel design of Mach Zehnder Interferometer (MZI) in terms of using special type of optical fiber that has double clad with graded distribution of the refractive index that can be easily implemented practically was suggested and simulated in this work. The suggested design is compact, rapid, and is simple to be modified and tested. The simulated design contains a MZI of 1546.74 nm of central wavelength that is constructed using special type of double clad optical fiber that has two different numerical apertures. The first aperture will supply single mode propagation via its core, while the second numerical aperture supports a zigzag wave propagation (multimode) in the first clad region. The interferometer’s

Cytokines are signaling molecules between inflammatory cells that play a significant role in the pathogenesis of a disease. Among these cytokines are interleukins (ILs) 17A and 33, and accordingly, the current case-control study sought to investigate the role of each of the two cytokines in the risk of developing multiple sclerosis (MS). Sixty-eight relapsing-remitting MS (RRMS) Iraqi patients and twenty healthy individuals (control group) were enrolled. Enzyme linked immunosorbent assay (ELISA) kits were used to determine serum levels of IL-17A and IL-33. Results revealed that IL-17A and IL-33 levels were significantly higher in MS patients than in controls (14.1 ± 4.5 vs. 7.5 ± 3.8 pg/mL; p < 0.001 and 65.3 ± 16

This study deals with the seismic reflection interpretation of lower Cretaceous Formations in Dhufria area, including structural and stratigraphic techniques. In the interpretation process, the 3-D seismic data volume and well logs have been used. Based on well logs and synthetic traces two horizons were identified and picked which are the top and bottom of Zubair Formation. These horizons were followed over all the area in order to obtain structural setting as well as studying Kirkuk group Formation of Tertiary age which represents highstand progradational seismic facies.

This research includes synthesis of new 5-Nitro isatin derivatives starting from 5-Nitro-3-(ethyl imino acetate)-2-oxo indole (1) namely 5-nitro-3-[(imino acetyl) semicarbazide]-2-oxo indole (2); 5-nitro-3-[(imino acetyl) phenylsemicarbazide]-2-oxo indole (3); 5-nitro-3-[(imino acetyl) thiosemicarbazide]-2-oxo indole (4); 5-nitro-3-[(iminoacetyl) phenylthiosemi carbazide]-2-oxo indole (5); 5-nitro-3-[(methyl imino)-4H-1, 2, 4-triazol-5-ol-3-yl]-2-oxo indole (6); 5-nitro-3-[(methyl imino) 4-phenyl-1, 2, 4-triazol-5-ol-3-yl]-2-oxo indole (7); 5-nitro-3-[(methyl imino) 4-phenyl-1, 2, 4-triazol-5-thiol-3-yl]-2-oxo indole (8) and 5-nitro-3-[(methyl imino) 4H-1, 2, 4-triazol-5-thiol-3-yl]-2-oxo indole (9). The derivatives were characterized us

Zinc sulfide (ZnS) thin films were deposited on glass substrates using pulsed laser deposition technique. The laser used is the Q-switched Nd: YAG laser with 1064nm wavelength and 1Hz pulse repetition rate and varying laser energy 700mJ-1000mJ with 25 pulse. The substrate temperature was kept constant at 100°C. The structural, morphological and optical properties of ZnS thin films were characterized with X-ray diffraction (XRD), scanning electron microscopy (SEM), atomic force microscope (AFM) and UV-VIS spectrophotometer.