Plumbago (Plumbaginaceae) is a genus of 10-20 species of flowering plants used in traditional Indian medicine, native to warm temperature to tropical regions of the world. The roots of Plumbago europaea, the Iraqi species of Plumbago, have been used for the treatment of cancer, rheumatoid arthritis, and dysmenorrhea. The main active constituents from dried powdered leaves and roots of Plumbago europaea were extracted by Soxhlet apparatus using ethyl acetate, the main active constituent was characterized by spectroscopic analysis (IR, ¹H NMR, and ¹³C NMR)   as plumbagin. Quantitative and qualitative study of plumbagin in the roots and leaves extracts was carried out by HP

The study aims to determine the concentrations of radon, humidity, and CO2 in residences within the Mitham Al-Tammar neighbourhood of Kufa, utilising an Airthings 2960 Wave Plus device in the living rooms of each household. The concentration of radon varied, with a minimum value of 13 ± 3.9 Bq/m³ and a maximum value of 90 ± 5.8 Bq/m³, yielding an average rate of 35.8 ± 4.889 Bq/m³. The concentrations of total VOCs in residences ranged from 69.26 ppb to 810.14 ppb, with a mean of 321.4855 ± 40.4. The humidity percentages exhibited a minimum concentration of 51.68% and a maximum of 122.97%, averaging 76.594 ± 4.298. The concentrations of volatile organic compounds and

The research aims at the possibility of measuring the technical and scale efficiency (SE) of the departments of the College of Administration and Economics at the University of Baghdad for a period lasting 8 years, from the academic year 2013-2014 to 2018-2019 using the method of Applied Data Analysis with an input and output orientation to maintain the distinguished competitive position and try to identify weaknesses in performance and address them. Nevertheless, the research problem lies in diagnosing the most acceptable specializations in the labor market and determining the reasons for students’ reluctance to enter some departments. Furthermore, the (Win4DEAp) program was used to measure technical and scale efficiency (SE) and rely on

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