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 local

This research deals with processing and Interpretation of Bouguer anomaly gravity field, using two dimensional filtering techniques to separate the residual gravity field from the Bouguer gravity map for a part of Najaf Ashraf province in Iraq. The residual anomaly processed in order to reduce noise and give a more comprehensive vision about subsurface linear structures. Results for descriptive interpretation presented as colored surfaces and contour maps in order to locate directions and extensions of linear features which may interpret as faults. A comparison among gravity residual field , 1st derivative and horizontal gradient made along a profile across the study area in order to assign the exact location of a major fault. Furthermor

Background: syndrome X or metabolic syndrome is a collection of multiple diseases mainly visceral obesity , hypertriglyceridemia , decrease HDL level, hypertension and elevated fasting blood glucose that lead to accelerated atherosclerosis through multiple mechanisms, one of the most important is increase inflammation of the vessels manifested by elevated high sensitivity C reactive protein (hs-CRP).Objective: The aim of the study was to assess the prevalence of elevatedhs CRP in people with metabolic syndrome and atherosclerosis complication (IHD, Cerebrovascular disease, peripheral vascular disease) and metabolic syndrome without these complication.Patients and methods:;This is a cross sectional study carried out in Diabetic referral c

Background: Fractures of the humeral shaft
accounting for approximately 3% of all
fractures. There is a wide array of good
options for their treatment and controversy
over the best methods. Although good
techniques of osteosynthesis are available, the
aim of this article is toemphasize on the benefit
and good outcome of conservative treatment
for properly selected cases to decrease the cost
and avoid the complications of surgery.

Background: Fractures of the humeral shaft accounting for approximately 3% of all fractures. There is a wide array of good options for their treatment and controversy over the best methods. Although good techniques of osteosynthesis are available, the aim of this article is toemphasize on the benefit and good outcome of conservative treatment for properly selected cases to decrease the cost and avoid the complications of surgery. Method : During the period from February 2011 to June 2012 fifty-five fractures of humeral shaft were treated at orthopedicdepartment in the ALKindyteaching hospital. 22 fractures considered suitable for the study. The patients treatedconservatively by using the‘U’ shaped coaptation slab. Then we shift to POP c

The study consists of video clips of all cars parked in the selected area. The studied camera height is1.5 m, and the video clips are 18video clips. Images are extracted from the video clip to be used for training data for the cascade method. Cascade classification is used to detect license plates after the training step. Viola-jones algorithm was applied to the output of the cascade data for camera height (1.5m). The accuracy was calculated for all data with different weather conditions and local time recoding in two ways. The first used the detection of the car plate based on the video clip, and the accuracy was 100%. The second is using the clipped images stored in the positive file, based on the training file (XML file), where the ac