Flow-production systems whose pieces are connected in a row may not have maintenance scheduling procedures fixed because problems occur at different times (electricity plants, cement plants, water desalination plants). Contemporary software and artificial intelligence (AI) technologies are used to fulfill the research objectives by developing a predictive maintenance program. The data of the fifth thermal unit of the power station for the electricity of Al Dora/Baghdad are used in this study. Three stages of research were conducted. First, missing data without temporal sequences were processed. The data were filled using time series hour after hour and the times were filled as system working hours, making the volume of the data relativel

Abstract:                                        

   We can notice cluster data in social, health and behavioral sciences, so this type of data have a link between its observations and we can express these clusters through the relationship between measurements on units within the same group.

    In this research, I estimate the reliability function of cluster function by using the seemingly unrelate

The study sought to highlight the importance of applying the administrative control procedures which play an important role in assessing the performance of the employees of the tax administration and specifically the companies department by setting the standards and objectives of the department on the basis of which in the implementation of its work and identify deviations and errors and find appropriate solutions and evaluate the results according to appropriate solutions, The study of the problem of research, namely the extent to which the tax administration applied to the administrative control procedures in view of its importance in evaluating the performance of its employees and the extent of their application to the legislations an

Abstract

          Binary logistic regression model used in data classification and it is the strongest most flexible tool in study cases variable response binary when compared to linear regression. In this research, some classic methods were used to estimate parameters binary logistic regression model, included the maximum likelihood method, minimum chi-square method, weighted least squares, with bayes estimation , to choose the best method of estimation by default values to estimate parameters according two different models of general linear regression models ,and different s

Finding a new source of resistance is important to reduce the use of synthetic pesticides, which can meet the global need of suppressing pollution. In this study, the resistance of eight eggplant cultivars to Aphis gossypii was evaluated. Results of the current study highlighted that the cultivar Long-Green has a very strong resistance after 14 days post infestation whereas Pearl-Round and White-Casper cultivars were susceptible. The rest of the tested cultivars (Green-oblong, Purple-panter, Paris, Ashbilia, and Barcelona) had mild resistance. Also, the study found significant differences between the infested and non-infested plants among the tested cultivars in the plant’s height, fresh-, and dry-weight. The susceptible cultivars

In this article, it is interesting to estimate and derive the three parameters which contain two scales parameters and one shape parameter of a new mixture distribution for the singly type one censored data which is the branch of right censored sample. Then to define some special mathematical and statistical properties for this new mixture distribution which is considered one of the continuous distributions characterized by its flexibility. Next,  using maximum likelihood estimator method for singly type one censored data based on the Newton-Raphson matrix procedure to find and estimate values of these three parameter by utilizing the real data taken from the National Center for Research and Treatment of Hematology/University of Mus

    This study was designed to investigate the capability of gram-negative bacteria that isolated form wound and burn infection to production of Biofilm which included (32) isolates, which have multi – drug resistant to antibiotics. The isolates included (10) Pseudomonas aeruginosa, (9) Klebsiella pneumoniae, (6) Escherichia coli, (5) Proteus mirabilis and (2) Enterobacter cloacae. The method used method links the crystal violet with biofilm and reading by ELISA which was adopted on the values of optical density of violets that linked to the mass of biofilm at the wavelength of (620) nm, the test results showed variation of biofilm composition for all bacterial species depending on the optical density value while th

This investigation was conducted to examine some physical and chemical properties of sand dunes collected from Basrah (1 '2 and 3) 'Nassiriya (4 and 5) and Amara (6) provinces that situated in lower Mesopotamia plain.

The results indicate clearly that the dominant particles in the samples were sand that were ranging from (81) % to (97) %, however the aggregated size of (0.1 - 0.25) mm were predominates in the investigated sand dunes of the region . Also the study shows that the content of the organic matter and potassium ions were very low (0.1- 0.4% '0.02 -0.22 meq I 100 gm soil. Further more the current result shows high a percentage of calcium carbonate (20.3 - 42.5%). In addition, the study has found a

Unconfined compressive strength (UCS) of rock is the most critical geomechanical property widely used as input parameters for designing fractures, analyzing wellbore stability, drilling programming and carrying out various petroleum engineering projects. The USC regulates rock deformation by measuring its strength and load-bearing capacity. The determination of UCS in the laboratory is a time-consuming and costly process. The current study aims to develop empirical equations to predict UCS using regression analysis by JMP software for the Khasib Formation in the Buzurgan oil fields, in southeastern Iraq using well-log data. The proposed equation accuracy was tested using the coefficient of determination (R²), the average absolute