Sensibly highlighting the hidden structures of many real-world networks has attracted growing interest and triggered a vast array of techniques on what is called nowadays community detection (CD) problem. Non-deterministic metaheuristics are proved to competitively transcending the limits of the counterpart deterministic heuristics in solving community detection problem. Despite the increasing interest, most of the existing metaheuristic based community detection (MCD) algorithms reflect one traditional language. Generally, they tend to explicitly project some features of real communities into different definitions of single or multi-objective optimization functions. The design of other operators, however, remains canonical lacking any inte

Objective: The aim of the present study is to assess the practices of nurses towards standard precautions at Azady
Teaching Hospital in the City of Kirkuk.
Methodology: A descriptive study, which uses the assessment approach and it was conducted on nurses from January
18th, 2009 to September 30th, 2009, using non-probability sampling a purposive sample of (37) subject (male and
female nurses) who worked at surgical wards in Azady Teaching Hospital in Kirkuk city was selected. Two study
instruments were utilized for proper data collection [questionnaire and observational checklist]; a questionnaire was
developed for the purpose of the study. It was comprised of two parts which included the nurses' demographic
characte

     Unknown subsurface leaking water sources and possible subsurface seepage from a sewage tank in a garden at Al-Khawarizmi engineering college, University of Baghdad, were detected in this study. The 2D electrical resistivity imaging. The ERI survey is carried out along two lines, 60m and 50m long, with an electrode spacing of 1 m, forming a cross using the Wenner-Schlumberger array configuration. Line 1 is 60m, while line 2 is 50m. Soil samples were collected from line 1 at positions of electrode 34, which shows a high resistivity value, and electrode 55, which shows low resistivity, for laboratory analysis. Robust inversion and modelling processes showed relative change and high contrast in interpreted resistivities. Soil analy

Abstract:

   Witness the current business environment changes rapidly reflected on the performance of the facility wishing to stay , which is no longer style reaction enough to handle installations with their environment , and quickly began to lose its luster with the emergence of a message and the vision of contemporary business environment from a set of parts interacting with each other and the concept of behavioral includes all dimensions of performance, it is imperative to adopt a system installations influence variables and positive interaction through the development of strategic plans and the use of implementation and follow-up strategies to ensure the effectiveness of the method for meas

     Smishing is a cybercriminal attack targeting mobile Short Message Service (SMS) devices that contains a malicious link, phone number, or email. The attacker intends to use this message to steal the victim's sensitive information, such as passwords, bank account details, and credit cards. One method of combating smishing is to raise awareness and educate users about the various tactics used by SMS phishers. But even so, this method has been criticized for becoming inefficient because smishing tactics are continually evolving. A more promising anti-smishing method is to use machine learning. This paper introduces a number of machine learning algorithms that can be used for detecting smishing. Furthermore, the differences and simil

Determining the face of wearing a mask from not wearing a mask from visual data such as video and still, images have been a fascinating research topic in recent decades due to the spread of the Corona pandemic, which has changed the features of the entire world and forced people to wear a mask as a way to prevent the pandemic that has calmed the entire world, and it has played an important role. Intelligent development based on artificial intelligence and computers has a very important role in the issue of safety from the pandemic, as the Topic of face recognition and identifying people who wear the mask or not in the introduction and deep education was the most prominent in this topic. Using deep learning techniques and the YOLO (”You on

Deepfake is a type of artificial intelligence used to create convincing images, audio, and video hoaxes and it concerns celebrities and everyone because they are easy to manufacture. Deepfake are hard to recognize by people and current approaches, especially high-quality ones. As a defense against Deepfake techniques, various methods to detect Deepfake in images have been suggested. Most of them had limitations, like only working with one face in an image. The face has to be facing forward, with both eyes and the mouth open, depending on what part of the face they worked on. Other than that, a few focus on the impact of pre-processing steps on the detection accuracy of the models. This paper introduces a framework design focused on this asp