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 linear segment with parabolic blend (LSPB) trajectory deviates from the specified waypoints. It is restricted to that the acceleration must be sufficiently high. In this work, it is proposed to engage modified LSPB trajectory with particle swarm optimization (PSO) so as to create through points on the trajectory. The assumption of normal LSPB method that parabolic part is centered in time around waypoints is replaced by proposed coefficients for calculating the time duration of the linear part. These coefficients are functions of velocities between through points. The velocities are obtained by PSO so as to force the LSPB trajectory passing exactly through the specified path points. Also, relations for velocity correction and exact v

Background Due to the intermittent, nonlinear, and uncertain behavior of renewable energy sources (res) such as solar and wind, grid stability and reliability require very high forecasting and optimization skills as widely reported in the literature. Traditional optimization methods work very well in small or static systems but are suffer difficulty on large-scale, dynamic and stochastic renewable environment due to their NP-hard nature. Methods The framework introduces the concept of a Machine Learning-Assisted Hybrid Cuckoo Search (ML-HCS) that combines CS with a hybrid metaheuristic and integrates Long Short-Term Memory (LSTM) networks for forecasting based on both regression models of LSTMs and hybrid optimization algorithm

Back ground: Visceral leishmaniasis is endemic in the
middle and south of Iraq, it involves mostly infants. The
disease is observed mainly among rural areas that are far
from equipped medical centers. Therefore, there is a need
for anon- invasive, cost- effective, reliable, easily
available and fast method of diagnosis of this dngerous
disease.
Objective: The aim was to compare the validity and
predictive values of the recombinant K39 antigen (rK39)
test with that of the indirect fluorescent antibody test
(IFAT) test (the usual laboratory method) in the detection
of visceral leishmaniasis.
Methods: A Cross-sectional study was done in ALMansour Pediatric Hospital (in AL-Rusafa), and Central
Pediatric

The present study was identified the type of bacterial contamination of Iraqi banknotes currency (Iraqi dinars) in circulation. 68 Iraqi banknotes currency of different denominations samples were randomly gathered from different locations and different occupational groups in Baghdad city. The results showed 61 (89.70%) of the samples were determined to be contaminated with bacteria, whereas 7 (10.29%) were confirmed to be sterile. A total of 11 different species of bacteria resulting in 72 isolates were found from those 61 contaminated Iraqi banknotes currency. Based on culture, morphological and biochemical tests, 11 isolates were identified as Bacillus sp., Staphylococcus aureus, Staphylococcus epidermidis, Corynebacterium diphtheria, Leu

In the present work, radon gas concentrations in different surface soil samples in Baghdad governorate were measured using RAD-7 detector. The results have been shown that, the Radon gas concentrations ranged between (41.67±1.78Bq/m3), to (185.67±4.22Bq/m3), a map showing the distribution of the concentration of radon in selected areas was defined to identify areas with high pollution level. The reason for the high concentration of radon is that these surface soil samples are taken from agricultural areas. It is also known that fertilizers contain uranium levels as well as areas bombed in wars in the country. It is worth noting that all radon concentrations in Baghdad governorate are below the recommended minimum of 200-300Bq/m3) (Inte

The ground level ozone concentration at different locations in Baghdad city was identified. Five
different sites have been chosen to identify the ground level ozone concentration. Al- Dora and Al-
Za'afarania were chosen as areas contained point source ( power plant station ) in addition to high traffic
load , while Al –Uma park, Aden square and Al-Mawal square were chosen as area contained heavy
traffic only (line source). The measurement focuses on spring and fall because these periods display
favorable meteorology to ozone formation. During the research period the maximum values (peaks) for
ground level ozone concentration were observed at fall: at Al-Za'afarania area 101ppb as an average, at
Al-Dora 87 ppb as a

Amaranthus viridis L. belongs to the Amaranthaceae family. It is a rich source of numerous phytochemicals and amino acids. The objective of this work was to optimize Ultrasound-Assisted Extraction (UAE) based on the extraction yield and Thin-Layer Chromatography (TLC) profile under different conditions, to compare the optimized UAE to the Soxhlet extraction method and evaluate the cytotoxic effects of the ethyl acetate fraction of the 80 % ethanolic extract on the SKGT-4 (human esophageal adenocarcinoma), AGS (human gastric adenocarcinoma) and A431 (human epidermoid carcinoma). A one-factor at a time experiment was carefully designed to assess the influence of the following factors on the extraction: time, frequency, solid-to-solven