The need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2,0,0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlation coefficient between the actual and predicted values for fluoride concentration at the six locations, Al-Karakh, East Tigris, Al-Wathbah, AL-Karamah, Al-Rashid and Al-Wahda WTP intakes, was 0.93, 0.82, 0.86, 0.90, 0.83 and 0.89, respectively. Model verification results indicated that the model forecasting outputs rationally estimated the actual monthly fluoride content in the selected locations.
The utilization of artificial intelligence techniques has garnered significant interest in recent research due to their pivotal role in enhancing the quality of educational offerings. This study investigated the impact of employing artificial intelligence techniques on improving the quality of educational services, as perceived by students enrolled in the College of Pharmacy at the University of Baghdad. The study sample comprised 379 male and female students. A descriptive-analytical approach was used, with a questionnaire as the primary tool for data collection. The findings indicated that the application of artificial intelligence methods was highly effective, and the educational services provided to students were of exceptional
... Show MoreThe optical detectors which had been used in medical applications, and especially in radioactive treatments, need to be modified studied for the effects of radiations on them. This study included preparation of the MnS thin films in a way that vacuum thermal evaporation process at room temperature 27°C with thickness (400+-10nm) nm and a sedimentation rate of 0.39nm/sec on glass floors. The thin films prepared as a detector and had to be treated with neutron irradiation to examine the results gained from this process. The results decay X-ray (XRD) showed that all the prepared thin films have a multi-crystalline structure with the dominance of the direction (111), the two samples were irradiated with a neutron irradiation source (241Am-9Be)
... Show MoreOver the years, the prediction of penetration rate (ROP) has played a key rule for drilling engineers due it is effect on the optimization of various parameters that related to substantial cost saving. Many researchers have continually worked to optimize penetration rate. A major issue with most published studies is that there is no simple model currently available to guarantee the ROP prediction.
The main objective of this study is to further improve ROP prediction using two predictive methods, multiple regression analysis (MRA) and artificial neural networks (ANNs). A field case in SE Iraq was conducted to predict the ROP from a large number of parame
These days, it is crucial to discern between different types of human behavior, and artificial intelligence techniques play a big part in that. The characteristics of the feedforward artificial neural network (FANN) algorithm and the genetic algorithm have been combined to create an important working mechanism that aids in this field. The proposed system can be used for essential tasks in life, such as analysis, automation, control, recognition, and other tasks. Crossover and mutation are the two primary mechanisms used by the genetic algorithm in the proposed system to replace the back propagation process in ANN. While the feedforward artificial neural network technique is focused on input processing, this should be based on the proce
... Show MoreAnalysis the economic and financial phenomena and other requires to build the appropriate model, which represents the causal relations between factors. The operation building of the model depends on Imaging conditions and factors surrounding an in mathematical formula and the Researchers target to build that formula appropriately. Classical linear regression models are an important statistical tool, but used in a limited way, where is assumed that the relationship between the variables illustrations and response variables identifiable. To expand the representation of relationships between variables that represent the phenomenon under discussion we used Varying Coefficient Models
... Show MoreIn this paper, a discussion of the principles of stereoscopy is presented, and the phases
of 3D image production of which is based on the Waterfall model. Also, the results are based
on one of the 3D technology which is Anaglyph and it's known to be of two colors (red and
cyan).
A 3D anaglyph image and visualization technologies will appear as a threedimensional
by using a classes (red/cyan) as considered part of other technologies used and
implemented for production of 3D videos (movies). And by using model to produce a
software to process anaglyph video, comes very important; for that, our proposed work is
implemented an anaglyph in Waterfall model to produced a 3D image which extracted from a
video.
Lacing reinforcement plays a critical role in the design and performance of reinforced concrete (RC) slabs by distributing the applied loads more evenly across the slab, ensuring that no specific area of the slab is overloaded. In this study, nine slabs, divided into three groups according to the investigated parameters, were meticulously designed and evaluated to study the interplay between the lacing reinforcement and other key parameters. Each slab was crafted for simple support and was subjected to both static and repeated two-point load tests. The lacing reinforcement had an angle of 45° with various tension and lacing steel. The repeated-tested specimens with lacing reinforcement experienced smaller ductility than those of s
... Show MoreLacing reinforcement plays a critical role in the design and performance of reinforced concrete (RC) slabs by distributing the applied loads more evenly across the slab, ensuring that no specific area of the slab is overloaded. In this study, nine slabs, divided into three groups according to the investigated parameters, were meticulously designed and evaluated to study the interplay between the lacing reinforcement and other key parameters. Each slab was crafted for simple support and was subjected to both static and repeated two-point load tests. The lacing reinforcement had an angle of 45° with various tension and lacing steel. The repeated-tested specimens with lacing reinforcement experienced smaller ductility than those of s
... Show MoreIn this paper, a new method of selection variables is presented to select some essential variables from large datasets. The new model is a modified version of the Elastic Net model. The modified Elastic Net variable selection model has been summarized in an algorithm. It is applied for Leukemia dataset that has 3051 variables (genes) and 72 samples. In reality, working with this kind of dataset is not accessible due to its large size. The modified model is compared to some standard variable selection methods. Perfect classification is achieved by applying the modified Elastic Net model because it has the best performance. All the calculations that have been done for this paper are in