Anomaly detection is still a difficult task. To address this problem, we propose to strengthen DBSCAN algorithm for the data by converting all data to the graph concept frame (CFG). As is well known that the work DBSCAN method used to compile the data set belong to the same species in a while it will be considered in the external behavior of the cluster as a noise or anomalies. It can detect anomalies by DBSCAN algorithm can detect abnormal points that are far from certain set threshold (extremism). However, the abnormalities are not those cases, abnormal and unusual or far from a specific group, There is a type of data that is do not happen repeatedly, but are considered abnormal for the group of known. The analysis showed DBSCAN using the

     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

In this work laser detection and tracking system (LDTS) is designed and implemented using a fuzzy logic controller (FLC). A 5 mW He-Ne laser system and an array of nine PN photodiodes are used in the detection system. The FLC is simulated using MATLAB package and the result is stored in a lock up table to use it in the real time operation of the system. The results give a good system response in the target detection and tracking in the real time operation.

The aim of this research is to determine the most important and main factors that lead to Preeclampsia. It is also about finding suitable solutions to eradicate these factors and avoid them in order to prevent getting Preeclampsia. To achieve this, a case study sample of (40) patients from Medical City - Oncology Teaching Hospital was used to collect data by a questionnaire which contained (17) reasons to be investigated. The statistical package (SPSS) was used to compare the results of the data analysis through two methods (Radial Bases Function Network) and (Factorial Analysis). Important results were obtained, the two methods determined the same factors that could represent the direct reason which causes Preecla

From different hospitals in Baghdad city, 25 clinical isolates of Proteus spp. were collected from different clinical samples, all isolates were identified as Proteus mirabilis by using bacteriological and biochemical assays in addition to Vitek-2 identification system. 15 (60%) isolates were identifying as Proteus mirabilis. The susceptibility of P. mirabilis isolates towards cefotaxime and ceftazidime was (66.6 %), (20%) consecutively; while extended spectrum β-lactamases producing P. mirabilis percentage was (30.7 %). Because blaVEB-1 was documented as an important indicator for increasing risk of extended spectrum beta ßlactamases producing P. mirabilis isolates that began to spread from many geographic area to Far east which inc

Background: Cholera has been recognized as a killer disease since earliest time. The disease is caused by infection of the small intestine by Vibrio cholerae O1 and O1391 which is characterized by severe dehydrating diarrheal condition and is one disease in modern times that is epidemic, endemic and pandemic in nature. Objective: This study was carried out to detect and isolate V. cholerae from patients suffered from watery diarrhea, which may cause severe complications such as dehydration, shock followed by death. Materials and methods: stool specimens were collected from 308 patients with watery diarrhea. These samples were tested with many criteria such as TCBS agar, gram stain, biochemical tests and VITEK-2 system to improve the isolati

The present study was Conducted to evaluate the effect of amixture of three species of arbuscular mycorrhizal fungi ( Glomus etunicatum , G. leptotichum and Rhizophagus intraradices ) in Influence on the percentage of the components of NPK and protein of tomato leaves and roots infected with Fusarium oxysporum f.sp. Lycopersici wich cause Fusarial wilt disease , planted for 8 weeks in the presence of the organic matter ( peatmose) , using pot cultures in aplastic green house , Results indicated significant increase in the percentage of the elements of NK and protein of tomato leaves and roots In the control treatment (C), While the percentage of the element P was after infection with the pathogen 4 weaks after mycorrhizal colonization in al