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 local

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

Human beings are greatly inspired by nature. Nature has the ability to solve very complex problems in its own distinctive way. The problems around us are becoming more and more complex in the real time and at the same instance our mother nature is guiding us to solve these natural problems. Nature gives some of the logical and effective ways to find solutions to these problems. Nature acts as an optimized source for solving the complex problems.  Decomposition is a basic strategy in traditional multi-objective optimization. However, it has not yet been widely used in multi-objective evolutionary optimization.   

Although computational strategies for taking care of Multi-objective Optimization Problems (MOPs) h

     Recently, Human Activity Recognition (HAR) has been a popular research field due to wide spread of sensor devices. Embedded sensors in smartwatch and smartphone enabled applications to use sensors in activity recognition with challenges for example, support of elderly’s daily life . In the aim of recognizing and analyzing human activity many approaches have been implemented in researches.  Most articles published on human activity recognition used a multi -sensors based methods where a number of sensors were tied on different positions on a human body which are not suitable for many users. Currently, a smartphone and smart watch device combine different types of sensors which present a new area for analysi

The aim of this research is to develop qualitative workouts based on certain sensory perceptions for the development of offensive basketball abilities and to determine their impact on female pupils. Several findings, based on the au-thor's extensive expertise instructing basketball materials and our closeness to the sample, revealed deficits in some sensory perceptions “in the game of basketball”, which impair the accuracy of passing the ball to the best team-mate. It also affects the pace of dribbling and the difficulty of selecting the op-timal moment and distance to fire. Therefore, the researcher designs qualita-tive activities based on many sensory experiences, including distance, speed, force, and direction shift. In addition, the

In this research, annealed nanostructured ZnO catalyst water putrefaction system was built using sun light and different wavelength lasers as stimulating light sources to enhance photocatalytic degradation activity of methylene blue (MB) dye as a model based on interfacial charges transfer. The structural, crystallite size, morphological, particle size, optical properties and degradation ability of annealed nanostructured ZnO were characterized by X-Ray Diffraction (XRD), Atomic Force Microscopy (AFM) and UV-VIS Spectrometer, respectively. XRD results demonstrated a pure crystalline hexagonal wurtzite with crystalline size equal to 23 nm. From AFM results, the average particle size was 79.25nm. All MB samples and MB with annealed nanostr

16S ribosomal RNA (16S rRNA) gene sequences used to study bacterial phylogeny and taxonomy have been by far the most common housekeeping genetic marker utilized for identification and ancestor determination. This study aimed to investigate, for the first time, the relationship between Klebsiella spp. isolated from clinical and environmental samples in Iraq.

Fifty Klebsiella spp. isolates were isolated from clinical and environmental sources. Twenty-five isolates were collected from a fresh vegetable (Apium graveolens) and 25 from clinical samples (sputum, wound swab, urine). Enteric bacteria were isolated on selective and differential media and identified by an automatic identification system, vitek-2.