In the current digitalized world, cloud computing becomes a feasible solution for the virtualization of cloud computing resources.  Though cloud computing has many advantages to outsourcing an organization’s information, but the strong security is the main aspect of cloud computing. Identity authentication theft becomes a vital part of the protection of cloud computing data. In this process, the intruders violate the security protocols and perform attacks on the organizations or user’s data. The situation of cloud data disclosure leads to the cloud user feeling insecure while using the cloud platform. The different traditional cryptographic techniques are not able to stop such kinds of attacks. BB84 protocol is the first quantum cry

       The most popular medium that being used by people on the internet nowadays is video streaming.  Nevertheless, streaming a video consumes much of the internet traffics. The massive quantity of internet usage goes for video streaming that disburses nearly 70% of the internet. Some constraints of interactive media might be detached; such as augmented bandwidth usage and lateness. The need for real-time transmission of video streaming while live leads to employing of Fog computing technologies which is an intermediary layer between the cloud and end user. The latter technology has been introduced to alleviate those problems by providing high real-time response and computational resources near to the

The aim of this research is to compare traditional and modern methods to obtain the optimal solution using dynamic programming and intelligent algorithms to solve the problems of project management.

It shows the possible ways in which these problems can be addressed, drawing on a schedule of interrelated and sequential activities And clarifies the relationships between the activities to determine the beginning and end of each activity and determine the duration and cost of the total project and estimate the times used by each activity and determine the objectives sought by the project through planning, implementation and monitoring to maintain the budget assessed 

This paper proposes a new strategy to enhance the performance and accuracy of the Spiral dynamic algorithm (SDA) for use in solving real-world problems by hybridizing the SDA with the Bacterial Foraging optimization algorithm (BFA). The dynamic step size of SDA makes it a useful exploitation approach. However, it has limited exploration throughout the diversification phase, which results in getting trapped at local optima. The optimal initialization position for the SDA algorithm has been determined with the help of the chemotactic strategy of the BFA optimization algorithm, which has been utilized to improve the exploration approach of the SDA. The proposed Hybrid Adaptive Spiral Dynamic Bacterial Foraging (HASDBF)

  Survival analysis is the analysis of data that are in the form of times from the origin of time until the occurrence of the end event, and in medical research, the origin of time is the date of registration of the individual or the patient in a study such as clinical trials to compare two types of medicine or more if the endpoint It is the death of the patient or the disappearance of the individual. The data resulting from this process is called survival times. But if the end is not death, the resulting data is called time data until the event. That is, survival analysis is one of the statistical steps and procedures for analyzing data when the adopted variable is time to event and time. It could be d

Background: Legionella pneumophila (L. pneumophila) is gram-negative bacterium, which causes Legionnaires’ disease as well as Pontiac fever. Objective: To determine the frequency of Legionella pneumophila in pneumonic patients, to determine the clinical utility of diagnosing Legionella pneumonia by urinary antigen testing (LPUAT) in terms of sensitivity and specificity, to compares the results obtained from patients by urinary antigen test with q Real Time PCR (RT PCR) using serum samples and to determine the frequency of serogroup 1 and other serogroups of L. pneumophila. Methods: A total of 100 pneumonic patients (community acquired pneumonia) were enrolled in this study during a period between October 2016 to April 2017; 92 sam

Excessive skewness which occurs sometimes in the data is represented as an obstacle against normal distribution. So, recent studies have witnessed activity in studying the skew-normal distribution (SND) that matches the skewness data which is regarded as a special case of the normal distribution with additional skewness parameter (α), which gives more flexibility to the normal distribution. When estimating the parameters of (SND), we face the problem of the non-linear equation and by using the method of Maximum Likelihood estimation (ML) their solutions will be inaccurate and unreliable. To solve this problem, two methods can be used that are: the genetic algorithm (GA) and the iterative reweighting algorithm (IR) based on the M