With the growth of mobile phones, short message service (SMS) became an essential text communication service. However, the low cost and ease use of SMS led to an increase in SMS Spam. In this paper, the characteristics of SMS spam has studied and a set of features has introduced to get rid of SMS spam. In addition, the problem of SMS spam detection was addressed as a clustering analysis that requires a metaheuristic algorithm to find the clustering structures. Three differential evolution variants viz DE/rand/1, jDE/rand/1, jDE/best/1, are adopted for solving the SMS spam problem. Experimental results illustrate that the jDE/best/1 produces best results over other variants in terms of accuracy, false-positive rate and false-negative

Plagiarism Detection Systems play an important role in revealing instances of a plagiarism act, especially in the educational sector with scientific documents and papers. The idea of plagiarism is that when any content is copied without permission or citation from the author. To detect such activities, it is necessary to have extensive information about plagiarism forms and classes. Thanks to the developed tools and methods it is possible to reveal many types of plagiarism. The development of the Information and Communication Technologies (ICT) and the availability of the online scientific documents lead to the ease of access to these documents. With the availability of many software text editors, plagiarism detections becomes a critical

The aquatic Heptageniidae family of Ava-sheen branch (Greater Zab Tributary) in Duhok Governorate/ Iraq was studied. Samples were collected using Surber stream sampler to study their diagnostic morphological characteristics and molecular phylogenetic profile using a nuclear gene 16s ribosomal RNA. The morphological and molecular identification supported that the three species, Epeorus longimanus, Heptagenia elegantula and Ephemerella cornutus belong to Heptageniidae family, while the molecular results also confirmed the monophyletic origin of these three genera.

      Under high concentrations of antibiotics, a fraction of the bacterial population exhibits a phenomenon known as persistence. Toxin- system (TA system) has been reported to be involved in the formation of E. coli, Mycobacterium, and S. aureus persisters.  In this study, the ability of thirty Iraqi isolates of MRSA to form in vitro persister cells after exposure to three different antibiotics (Ceftriaxone 30 µg, Mecillinam 10 µg, and Mupirocin 20 µg) was examined by TD test. Additionally, efflux pump inhibitor [Fluphenazine 0.25 mg/ml] was combined with the antibiotic that triggered persister formation. The distribution of mazEF and yefM-yoeB (Type II TA system) in the tested isolates was detected by PCR. 91% of Mupirocin su

Heart sound is an electric signal affected by some factors during the signal's recording process, which adds unwanted information to the signal. Recently, many studies have been interested in noise removal and signal recovery problems. The first step in signal processing is noise removal; many filters are used and proposed for treating this problem. Here, the Hankel matrix is implemented from a given signal and tries to clean the signal by overcoming unwanted information from the Hankel matrix. The first step is detecting unwanted information by defining a binary operator. This operator is defined under some threshold. The unwanted information replaces by zero, and the wanted information keeping in the estimated matrix. The resulting matrix

Anomaly detection is still a difficult task. To address this problem, we propose to strengthen DBSCAN algorithm for the data by converting all data to the graph concept frame (CFG). As is well known that the work DBSCAN method used to compile the data set belong to the same species in a while it will be considered in the external behavior of the cluster as a noise or anomalies. It can detect anomalies by DBSCAN algorithm can detect abnormal points that are far from certain set threshold (extremism). However, the abnormalities are not those cases, abnormal and unusual or far from a specific group, There is a type of data that is do not happen repeatedly, but are considered abnormal for the group of known. The analysis showed DBSCAN using the

     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