Recurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning al

The constructivist learning model is one of the models of constructivist theory in learning, as it generally emphasizes the active role of the learner during learning, in addition to that the intellectual and actual participation in the various activities to help students gain the skills of analyzing artistic works. The current research aims to know the effectiveness of the constructivist learning model in the acquisition of the skills of the Institute of Fine Arts for the skills of (technical work analysis). To achieve the goal, the researcher formulated the following hypothesis: There are no statistically significant differences between the average scores of the experimental group students in the skill test for analyzing artworks befor

Background: Pain due to muscular cramp during hemodialysis is one of the most common problems experienced by patient undergoing hemodialysis, and is associated with poor outcomes of patients. The main aim of this study was to comparing the effects of lavender oil and olive oil massage on Pain due to muscular cramp during hemodialysis.

Methods: In this random clinical trial, 60 hemodialysis patients were enrolled randomly and allocated to two groups with 30 members in Lordegan and Brojen hospitals, Shahrekord, Iran. The intervention included flora massage on the lower leg muscles so that the first group received olive oil massage (10 drops) and the second group received lavender oil massage (10 dr

Abstract

The current research aims to identify the negotiation behavior of administrative teachers, as well as to identify the significance of the differences in negotiation behavior according to the variables (gender, scientific title, length of service). After confirming the psychometric characteristics of (20) items, the researchers applied the scale to (400) male and female administrative teaching staff who were randomly selected from the University of Baghdad for the academic year 2021/2022. The results showed the following the research sample has a negotiating behavior. There are no statistically significant differences between gender, scientific title, and length of service in the means of negotiating beha

There has been a growing interest in the use of chaotic techniques for enabling secure communication in recent years. This need has been motivated by the emergence of a number of wireless services which require the channel to provide low bit error rates (BER) along with information security. The aim of such activity is to steal or distort the information being conveyed. Optical Wireless Systems (basically Free Space Optic Systems, FSO) are no exception to this trend. Thus, there is an urgent necessity to design techniques that can secure privileged information against unauthorized eavesdroppers while simultaneously protecting information against channel-induced perturbations and errors. Conventional cryptographic techniques are not designed

Endoscopy is a rapidly growing field of Neurosurgery, it is defined as the applying of endoscope to treat different conditions of brain pathology within cerebral ventricular system and beyond it, endoscopic procedures performed by using different equipment and recording system to make a better visualization enhancing the surgeon's view by increasing illumination and magnification to look around corner and to capture image on video or digital format for later studies.

Botnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet