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

Capparis spinosa is one of the oldest genera grown in Iraqi land with worldwide traditional medicinal uses beside the culinary uses. These uses were own to the presence of many phytochemical including flavonoids, polyphenols. Among the reported polyphenolic acids are caffeic, chlorogenic and ferulic acids with well-known powerful antioxidant properties. The present work aimed to identify the presence of these polyphenolic acids in Iraqi caper naturally gown in the rural area of middle Iraq following standard chromatographic procedures. Aerial parts of the plant (buds, berries and leaves) were extracted with hydroalcoholic solvent by maceration method. Thin layer chromatographic techniques and HPLC analysis were performed to iden

     By definition, the detection of protein complexes that form protein-protein interaction networks (PPINs) is an NP-hard problem. Evolutionary algorithms (EAs), as global search methods, are proven in the literature to be more successful than greedy methods in detecting protein complexes. However, the design of most of these EA-based approaches relies on the topological information of the proteins in the PPIN. Biological information, as a key resource for molecular profiles, on the other hand, acquired a little interest in the design of the components in these EA-based methods. The main aim of this paper is to redesign two operators in the EA based on the functional domain rather than the graph topological domain. The perturb

Evolutionary algorithms are better than heuristic algorithms at finding protein complexes in protein-protein interaction networks (PPINs). Many of these algorithms depend on their standard frameworks, which are based on topology. Further, many of these algorithms have been exclusively examined on networks with only reliable interaction data. The main objective of this paper is to extend the design of the canonical and topological-based evolutionary algorithms suggested in the literature to cope with noisy PPINs. The design of the evolutionary algorithm is extended based on the functional domain of the proteins rather than on the topological domain of the PPIN. The gene ontology annotation in each molecular function, biological proce

Several studies have indicated that more than 600 cities in the world (intermas of rapid growth and development) will generate about 60% of international economic growth between 2010 and 2025 . by 2025 , 66% of the worlds population will live in urban areas the management of cities will face challenges that accompany this increase in the population which requires preparing to face these challenges and problems and the need to provide the aim of the research to know the readiness of Baghdad city to implement the strategies of urban management throught on asmple representing the ( Advisiry group for the comprechnsive development plan for the city of Baghdad 2030 and its supporters ) in the municipality of Baghdad and the number of

Urinary Schistosomiasis is one of important diseases that cause irritation and damage of urinary tract and other systems and tissues and can not be expected by doctors when diagnosing urinary tract diseases.The current study is conducted to investigate the prevalence of schistosomiasisin Baghdad / Al-Rusafa. 191urine samples were collected fromresidents ofsome areas of Al-Rusafain Baghdad governarate (Almashtal, Albaladyat, Alameen, Baghdad aljadida and Alnahrawan) for the period from March until the end of September 2010.The samples were examined by the precipitation and examination of micro hematuria by reagent strips. The total infection percentage was 9.42% (18/191) and was significantly higher in males compared tofemales12.64% (11/87)