This current study aims to:
1st: The recognizing of Alexithymia level for 6th grade students (Study Specimen) through the next Zero Hypothesis:1. There are no statistically significant differences at (0.05) level between the arithmetic mean of the specimen degrees as a whole and the central assumption for the scale of the lack in emotions expression
2. There are no statistically significant differences at (0.05) level between the arithmetic mean of the male students specimen and the arithmetic meanc of the female students specimen for the scale of Alexithymia.
2nd: ldentification the level of the emotional intelligence among 6th grade students (Study Specimen) through the next Zero Hypothesis:
1) There are no statistically si
Metaheuristic is one of the most well-known fields of research used to find optimum solutions for non-deterministic polynomial hard (NP-hard) problems, for which it is difficult to find an optimal solution in a polynomial time. This paper introduces the metaheuristic-based algorithms and their classifications and non-deterministic polynomial hard problems. It also compares the performance of two metaheuristic-based algorithms (Elephant Herding Optimization algorithm and Tabu Search) to solve the Traveling Salesman Problem (TSP), which is one of the most known non-deterministic polynomial hard problems and widely used in the performance evaluations for different metaheuristics-based optimization algorithms. The experimental results of Ele
... Show MoreThe nature of the dark sector of the Universe remains one of the outstanding problems in modern cosmology, with the search for new observational probes guiding the development of the next generation of observational facilities. Clues come from tension between the predictions from Λ cold dark matter (ΛCDM) and observations of gravitationally lensed galaxies. Previous studies showed that galaxy clusters in the ΛCDM are not strong enough to reproduce the observed number of lensed arcs. This work aims to constrain the warm dark matter (WDM) cosmologies by means of the lensing efficiency of galaxy clusters drawn from these alternative models. The lensing characteristics of two samples of simulated clusters in the Λ warm dark matter and ΛCDM
... Show MoreCOVID-19 affected the entire world due to the unavailability of the vaccine. The social distancing was a contributing factor that gave rise to the usage of Online Social Networks. It has been seen that people share the information that comes to them without verifying its source . One of the common forms of information that is disseminated that have a radical purpose is propaganda. Propaganda is organized and conscious method of molding conclusions and impacting an individual's contemplations to accomplish the ideal aim of proselytizer. For this paper, different propagandistic tweets were shared in the COVID-19 Era. Data regarding COVID-19 propaganda was extracted from Twitter. Labelling of data was performed manually using diffe
... Show MoreIn this paper, one of the Machine Scheduling Problems is studied, which is the problem of scheduling a number of products (n-jobs) on one (single) machine with the multi-criteria objective function. These functions are (completion time, the tardiness, the earliness, and the late work) which formulated as . The branch and bound (BAB) method are used as the main method for solving the problem, where four upper bounds and one lower bound are proposed and a number of dominance rules are considered to reduce the number of branches in the search tree. The genetic algorithm (GA) and the particle swarm optimization (PSO) are used to obtain two of the upper bounds. The computational results are calculated by coding (progr
... Show MoreThe Internet of Things (IoT) is a network of devices used for interconnection and data transfer. There is a dramatic increase in IoT attacks due to the lack of security mechanisms. The security mechanisms can be enhanced through the analysis and classification of these attacks. The multi-class classification of IoT botnet attacks (IBA) applied here uses a high-dimensional data set. The high-dimensional data set is a challenge in the classification process due to the requirements of a high number of computational resources. Dimensionality reduction (DR) discards irrelevant information while retaining the imperative bits from this high-dimensional data set. The DR technique proposed here is a classifier-based fe
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