The research aims to develop and build a plasma jet system operating under atmospheric pressure.for biological purposes. The advanced plasma system consists of a power supply and a plasma torch. The source of the development of the system is a previous laboratory system that was developed by changing the voltage and frequency of the power supply, as the power provider equips the system with a voltage in the form of a sine wave whose value is fixed at about (7.5kV) peak to peak and its frequency is about (28 kHz). The plasma torch consists of a teflon tube with of width of (10 m ) located at (10mm)  from the end of the tube. The current waveform and voltage wave were measured using a current and voltage sensor and an oscilloscop

In this paper, we introduce a new type of Drazin invertible operator on Hilbert spaces, which is called D-operator. Then, some properties of the class of D-operators are studied. We prove that the D-operator preserves the scalar product, the unitary equivalent property, the product and sum of two D-operators are not D-operator in general but the direct product and tenser product is also D-operator.

The Present study investigated the drought in Iraq, by using the rainfall data which obtained from 39 meteorological stations for the past 30 years (1980-2010). The drought coefficient calculated on basis of the standard precipitation index (SPI) and then characteristics of drought magnitude, duration and intensity were analyzed. The correlation and regression between magnitude and duration of drought were obtained according the (SPI) index. The result shows that drought magnitude values were greater in the northeast region of Iraq. 

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