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

The best proximity point is a generalization of a fixed point that is beneficial when the contraction map is not a self-map. On other hand, best approximation theorems offer an approximate solution to the fixed point equation . It is used to solve the problem in order to come up with a good approximation. This paper's main purpose is to introduce new types of proximal contraction for nonself mappings in fuzzy normed space and then proved the best proximity point theorem for these mappings. At first, the definition of fuzzy normed space is given. Then the notions of the best proximity point and - proximal admissible in the context of fuzzy normed space are presented. The notion of α ̃–ψ ̃- proximal contractive mapping is introduced.

This paper proposes two hybrid feature subset selection approaches based on the combination (union or intersection) of both supervised and unsupervised filter approaches before using a wrapper, aiming to obtain low-dimensional features with high accuracy and interpretability and low time consumption. Experiments with the proposed hybrid approaches have been conducted on seven high-dimensional feature datasets. The classifiers adopted are support vector machine (SVM), linear discriminant analysis (LDA), and K-nearest neighbour (KNN). Experimental results have demonstrated the advantages and usefulness of the proposed methods in feature subset selection in high-dimensional space in terms of the number of selected features and time spe

The covid-19 pandemic sweeping the world and has rendered a large proportion of the workforce as they are unable to commute to work. This has resulted in employees and employers seeking alternative work arrangements, including the software industry. Then comes the need for the global market and international presence of many companies to implement the global virtual teams (GVTs). GVTs members are gradually engaged in globalized business environments across space, time and organizational boundaries via information and communication technologies. Despite the advancement of technology, the project managers are still facing many challenges in communication. Hense, to become a successful project manager still a big challenge for them. This study

This paper deals with a central issue in the field of human communication and reveals the roaming monitoring of the incitement and hatred speech and violence in media, its language and its methods. In this paper, the researcher seeks to provide a scientific framework for the nature of the discourse of incitement, hatred speech, violence, and the role that media can play in solving conflicts with their different dimensions and in building community peace and preventing the emergence of conflicts among different parties and in different environments. In this paper, the following themes are discussed:
The root of the discourse of hatred and incitement
The nature and dimensions of the discourse of incitement and hatred speech
The n

Purpose: This study's objective is to assess this relationship in the context of the banking industry in Iraq. The human resources management practices (HRMPs) Theoretical framework: in this study included recruiting and selection, training and development, performance appraisal, compensation and reward to testing relationship HRMPs. Design/methodology/approach: in this study; We analysed by used a quantitative approach, and 246 employees were selected as a sample and given a questionnaire. The SPSS software was used to examine the data that were obtained from the questionnaire. Findings: The study's findings revealed a variety of hypotheses and conclusions, including the following: competitive advantage (CA) is positively impacted by

Background :Evening preparation for colonoscopy is often unsatisfactory and inconvenient. This study was performed to compare the efficacy of bowel preparation at two different timings: night before and morning of endoscopy and to compare the cecal intubation rate and disturbance of sleep hours between these two groups.
Methods: In this prospective randomized endoscopist- blinded trial, 150 patients were enrolled between March 2010 and August 2011. Patients aged between 18 to 80 years needing colonoscopy were included. Patients with prior bowel surgery, suspected bowel obstruction or those who didn't completely fulfill the preparation instructions were excluded. Patients received polyethyelen glycol electrolyte preparation in a mornin

The downhole flow profiles of the wells with single production tubes and mixed flow from more than one layer can be complicated, making it challenging to obtain the average pressure of each layer independently.  Production log data can be used to monitor the impacts of pressure depletion over time and to determine average pressure with the use of Selective Inflow Performance (SIP). The SIP technique provides a method of determining the steady state of inflow relationship for each individual layer. The well flows at different stabilized surface rates, and for each rate, a production log is run throughout the producing interval to record both downhole flow rates and flowing pressure. PVT data can be used to convert measured in-situ rates