Objectives: Assessment outcome of DOTS (Directly observed therapy short course) program in Al-Sader City
Sector that was established by the WHO.
Methodology: Three cohorts groups of patients attending Baghdad TB institute and TB center in Al-Sader city
were followed retrospectively. The 1st cohort included (314) patients registered in year (2003), the 2nd cohort
included (327) patients registered in year (2004), the 3rd cohort included (321) patients registered in year
(2005). The collected data were analyzed for case detection, treatment outcomes, retreatment outcomes,
treatment success, and retreatment success in regard to time, age and sex.
Results: The following rates were extracted for the three cohort: Case det

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

Heart sound is an electric signal affected by some factors during the signal's recording process, which adds unwanted information to the signal. Recently, many studies have been interested in noise removal and signal recovery problems. The first step in signal processing is noise removal; many filters are used and proposed for treating this problem. Here, the Hankel matrix is implemented from a given signal and tries to clean the signal by overcoming unwanted information from the Hankel matrix. The first step is detecting unwanted information by defining a binary operator. This operator is defined under some threshold. The unwanted information replaces by zero, and the wanted information keeping in the estimated matrix. The resulting matrix

     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

The aim of this study is to detect the level of psychological stress among unemployed individuals and the level of their wellbeing by finding the correlation between these two variables.

          The research sample consisted of (99) people who are currently unemployed and registered at the Ministry of Labor Affairs.

Schafer (1996) scale for psychological stress was used and alongside Ziout's (2012) scale for wellbeing.

          The results of the research showed an inverse relation between being unemployed and having wellbeing.

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