Background: The Covid-19 pandemic changed the world; its most important achievement for education was changing the approach from traditional to virtual education. The present study aimed to investigate the role of virtual education networks on mental health of students including personality, beliefs, scientific, and cultural dimensions, in selected countries.Methods: This was an exploratory and applied study. According to the phenomenology strategy, theoretical saturation occurred after 24 semi-structured and targeted qualitative interviews with teachers from Iran, Iraq, Syria and Lebanon, in 2023. Quantitative data was collected through a researcher-made online questionnaire with 423 participants. Teachers with at least a Bachelor’s degr

Software-defined networking (SDN) is an innovative network paradigm, offering substantial control of network operation through a network’s architecture. SDN is an ideal platform for implementing projects involving distributed applications, security solutions, and decentralized network administration in a multitenant data center environment due to its programmability. As its usage rapidly expands, network security threats are becoming more frequent, leading SDN security to be of significant concern. Machine-learning (ML) techniques for intrusion detection of DDoS attacks in SDN networks utilize standard datasets and fail to cover all classification aspects, resulting in under-coverage of attack diversity. This paper proposes a hybr

<p>Currently, breast cancer is one of the most common cancers and a main reason of women death worldwide particularly in<strong> </strong>developing countries such as Iraq. our work aims to predict the type of tumor whether benign or malignant through models that were built using logistic regression and neural networks and we hope it will help doctors in detecting the type of breast tumor. Four models were set using binary logistic regression and two different types of artificial neural networks namely multilayer perceptron MLP and radial basis function RBF. Evaluation of validated and trained models was done using several performance metrics like accuracy, sensitivity, specificity, and AUC (area under receiver ope

Despite the broad approbation of additive manufacturing technologies over diverse industries, printed parts’ performance, quality, and related build time are still greatly influenced by printing parameters. These parameters majorly affect mechanical strength, surface finish, dimensional accuracy, and overall production time of the printed part. Customized 3D printing layer thickness, speed, and acceleration are crucial parameters that affect the speedy printing process and final product quality. The current work considers layer thickness in addition to speed and high acceleration values effect on the surface quality, surface roughness and productivity time of 3D printed Polylactic Acid (PLA). The experimental methodology implemented withi

In this article, the detailed information was presented about azo-dyes, including a general description of this class of compounds, which included a historical overview, observations on the chemical structure of these compounds, particularly focusing on the azo group (-N=N-) responsible for their coloring properties. In addition, we provided a schematic of the first synthesized azo-compound. Furthermore, we mentioned the general properties of them and viewed a detailed explanation for the categorization of them either aliphatic or aromatic, subdivisions for each category or which category is the most widespread, and then illustrated the types for this class of organic compounds. The effective operator in these compounds called diazonium-sal

Background: Inflammation of the brain parenchyma brought on by a virus is known as viral encephalitis. It coexists frequently with viral meningitis and is the most prevalent kind of encephalitis. Objectives: To throw light on viral encephalitis, its types, epidemiology, symptoms and complications. Results: Although it can affect people of all ages, viral infections are the most prevalent cause of viral encephalitis, which is typically seen in young children and old people. Arboviruses, rhabdoviruses, enteroviruses, herpesviruses, retroviruses, orthomyxoviruses, orthopneumoviruses, and coronaviruses are just a few of the viruses that have been known to cause encephalitis. Conclusion: As new viruses emerge, diagnostic techniques advan

Objective(s): The world of dentistry is constantly evolving, and with the advent of 3D printing technology, the possibilities are endless. However, little is known about the effects of adding ZrO2 NPs to the denture base resin of 3D additive manufacturing technique.Aim of this study is to evaluate the behavior of resin which is used to 3D printing of denture base with the addition of ZrO2 NPs on denture adaptation property and diametral compression strength.Methods: 60 samples were printed, 30 disks for diametral compressive test and 30 denture base for denture adaptation test. Three groups per test (n=10). The control group for each test included unreinforced 3Dprinted denture base resin, and the other groups were  reinforced with (2&

In this paper, chip and powder copper are used as reinforcing phase in polyester matrix to form composites. Mechanical properties such as flexural strength and impact test of polymer reinforcement copper (powder and chip) were done, the maximum flexural strength for the polymer reinforcement with copper (powder and chip) are (85.13 Mpa) and (50.08 Mpa) respectively was obtained, while the maximum observation energy of the impact test for the polymer reinforcement with copper (powder and chip) are (0.85 J) and (0.4 J) respectively  

Computer systems and networks are being used in almost every aspect of our daily life, the security threats to computers and networks have increased significantly. Usually, password-based user authentication is used to authenticate the legitimate user. However, this method has many gaps such as password sharing, brute force attack, dictionary attack and guessing. Keystroke dynamics is one of the famous and inexpensive behavioral biometric technologies, which authenticate a user based on the analysis of his/her typing rhythm. In this way, intrusion becomes more difficult because the password as well as the typing speed must match with the correct keystroke patterns. This thesis considers static keystroke dynamics as a transparent layer of t

Localization is an essential demand in wireless sensor networks (WSNs). It relies on several types of measurements. This paper focuses on positioning in 3-D space using time-of-arrival- (TOA-) based distance measurements between the target node and a number of anchor nodes. Central localization is assumed and either RF, acoustic or UWB signals are used for distance measurements. This problem is treated by using iterative gradient descent (GD), and an iterative GD-based algorithm for localization of moving sensors in a WSN has been proposed. To localize a node in 3-D space, at least four anchors are needed. In this work, however, five anchors are used to get better accuracy. In GD localization of a moving sensor, the algo