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

Cryptography is the process of transforming message to avoid an unauthorized access of data. One of the main problems and an important part in cryptography with secret key algorithms is key. For higher level of secure communication key plays an important role. For increasing the level of security in any communication, both parties must have a copy of the secret key which, unfortunately, is not that easy to achieve. Triple Data Encryption Standard algorithm is weak due to its weak key generation, so that key must be reconfigured to make this algorithm more secure, effective, and strong. Encryption key enhances the Triple Data Encryption Standard algorithm securities. This paper proposed a combination of two efficient encryption algorithms

In this paper, the Azzallini’s method used to find a weighted distribution derived from the standard Pareto distribution of type I (SPDTI) by inserting the shape parameter (θ) resulting from the above method to cover the period (0, 1] which was neglected by the standard distribution. Thus, the proposed distribution is a modification to the Pareto distribution of the first type, where the probability of the random variable lies within the period  The properties of the modified weighted Pareto distribution of the type I (MWPDTI) as the probability density function ,cumulative distribution function, Reliability function , Moment and  the hazard function are found. The behaviour of probability density function for MWPDTI distrib

One of the scientific education aims, preparing a student able to keep up with the scientific developments and innovations around him and make him contribute, adapt, investment and continue development. The concepts of nanotechnology from scientific innovation open up an important area of thinking and intervention in the field of chemistry applications in daily life, the technological changes lead to social, political and economic changes which result that the students to have the knowledge, understanding, awareness, appreciation and sense in applications of modern technology for their use optimally, in order to cope with these scientific and technological changes. The research aims at finding out the correlation between the acquisi

Abstract:

Robust statistics Known as, resistance to errors caused by deviation from the stability hypotheses of the statistical operations (Reasonable, Approximately Met, Asymptotically Unbiased, Reasonably Small Bias, Efficient ) in the data selected in a wide range of probability distributions whether they follow a normal distribution or a mixture of other distributions deviations different standard .

power spectrum function lead to, President role in the analysis of Stationary random processes, form stable random variables organized according to time, may be discrete random variables or continuous. It can be described by measuring its total capacity as function in frequency.

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      In this study, the plasma formed by the preparation of Se and Tin (Sn) using a Nd: YAG laser with a wavelength of 1064 nm in air, which was then studied using the technique of optical emission spectrum, was presented (OES).The laser-induced plasma parameters such an electron temperature (Te) were identified using two-ratio methods, using Stark broadening methods to determine the density of electrons (n_e). According to the findings, there is a correlation between the amount of laser energy that is applied and the increase in the emission intensity of the spectral lines. In the case of Se plasma, an increase in laser energy causes a rise in the temperature of the electrons. While increasing the temperature of the elec

In this paper, we will illustrate a gamma regression model assuming that the dependent variable (Y) is a gamma distribution and that it's mean ( ) is related through a linear predictor with link function which is identity link function g(μ) = μ. It also contains the shape parameter which is not constant and depends on the linear predictor and with link function which is the log link and we will estimate the parameters of gamma regression by using two estimation methods which are The Maximum Likelihood and the Bayesian and a comparison between these methods by using the standard comparison of average squares of error (MSE), where the two methods were applied to real da

The immune infertility caused by anti-sperm antibodies (ASAs) represented about 10–20% of infertility among the couples. The ASAs interfere with sperm parameters such as sperm motility and sperm ability to penetrate cervical mucus, sperm-oocyte binding, and fertilization and embryo development. Objectives: The present study designed to assess semen analysis, presence of ASAs and DNA fragmentation index as well as correlation within these parameters in normzoospermic Iraqi subjects Patients, Materials, and Methods: A total number of Iraqi subjects (116) with range of age (20-51) years and their mean duration of infertility (4.70 ± 2.77). Seminal fluid for macroscopic and microscopic assessments done according to WHO 2010 criteria. The

In this paper, the error distribution function is estimated for the single index model by the empirical distribution function and the kernel distribution function. Refined minimum average variance estimation (RMAVE) method is used for estimating single index model. We use simulation experiments to compare the two estimation methods for error distribution function with different sample sizes, the results show that the kernel distribution function is better than the empirical distribution function.