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

 A total of 1453 freshwater fishes, belonging to 14 species of the
family Cyprinidae was collected from Lesser Zab and Greater Zab
rivers in north of Iraq during the period from November 2000 to the
end of November 2001. The inspection of skin, gills and different
internal organs revealed the infection of these fishes with a total of 14
species of Myxobolus which included seven species that represented
their first record in Iraq. These species included M. bulbocordis from
both Barbus sharpeyi and Chondrostoma regium; M. karuni from B
grypus; M. mesopotamiae from B. luteus; M. molnári from B
esocinus; M. pcrsicus from both B. grypus and Cyprinion macrostomum;
M.  Shaagani from both B. b

The aim of the research is to know the level of time management application and its impact on the performance of the job, a survey search in the general company for communication and information technology and provide recommendations that help employees to optimize the use of time and improve performance, which is an important element in controlling the various functions of the company. In order to achieve the objectives of the research, the questionnaire was based on two main variables and distributed to a random sample of (44) employees in the company out of (308) employees, thus the proportion of the sample (14%). After collecting the samples from the sample, there are (6) incomplete forms that have been retri

Abstract

The current research aims to develop a guidance program suitable for high school students and apply it to them in order to ensure the reduction of addiction to the use of different means of communication. The researchers used the scale of addiction to the means of communication (SAS) to measure the level of addiction as well as to identify the impact of the proposed guidance program in reducing the degree of addiction to communication. It was applied to a sample of (20) female students divided equally into two groups: an experimental group of (10) female students and a control group of (10) female students from the secondary level in a school under the department of education in the education of the alma

The phenomenon of negative behavior has studied as a social and psychological phenomenon that effect on the performance and life of workers inside and outside the organization. The adoption of this phenomenon is studied in terms of the role of the internal environment of the organization in addressing this behavior, being the variables belong to the field of organizational behavior to see the results of those variables on the Iraqi organizations, since the specificities of it differ from the rest of the Arab and foreign environments. Therefore, this study focused on testing the relationship of the internal environment of the organization and its role in addressing the negative behavior of the workers.

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Cryptocurrency became an important participant on the financial market as it attracts large investments and interests. With this vibrant setting, the proposed cryptocurrency price prediction tool stands as a pivotal element providing direction to both enthusiasts and investors in a market that presents itself grounded on numerous complexities of digital currency. Employing feature selection enchantment and dynamic trio of ARIMA, LSTM, Linear Regression techniques the tool creates a mosaic for users to analyze data using artificial intelligence towards forecasts in real-time crypto universe. While users navigate the algorithmic labyrinth, they are offered a vast and glittering selection of high-quality cryptocurrencies to select. The

This paper proposes a better solution for EEG-based brain language signals classification, it is using machine learning and optimization algorithms. This project aims to replace the brain signal classification for language processing tasks by achieving the higher accuracy and speed process. Features extraction is performed using a modified Discrete Wavelet Transform (DWT) in this study which increases the capability of capturing signal characteristics appropriately by decomposing EEG signals into significant frequency components. A Gray Wolf Optimization (GWO) algorithm method is applied to improve the results and select the optimal features which achieves more accurate results by selecting impactful features with maximum relevance