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.
Diyala Governorate was recently exposed to high flood waves discharged from Hemrin Dam. Since the dam was at its full capacity during the flood period, these waves were discharged to the Diyala River. Because of the reduction in Diyala River capacity to 750m3/s, the cities and villages on both sides of the river banks were inundated. Thus, the study's objective is to design a flood escape out of the Diyala River, to discharge the flood wave through it. The flood escape simulation was done by using HEC- RAS software. Two hundred twenty-three cross sections for the escape and 30 cross-sections of the Diyala River were used as geometric data. Depending on the geological formation that the escape passed t
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The optical absorption data of Hydrogenated Amorphous Silicon was analyzed using a Dunstan model of optical absorption in amorphous semiconductors. This model introduces disorder into the band-band absorption through a linear exponential distribution of local energy gaps, and it accounts for both the Urbach and Tauc regions of the optical absorption edge.Compared to other models of similar bases, such as the O’Leary and Guerra models, it is simpler to understand mathematically and has a physical meaning. The optical absorption data of Jackson et al and Maurer et al were successfully interpreted using Dunstan’s model. Useful physical parameters are extracted especially the band to the band energy gap , which is the energy gap in the a
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The method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par
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The problem of the study is to monitor the content presented in the Iraqi satellite channels to identify the nature of the ideas contained in these ads and to identify the values carried by the creative strategies and ad campaigns that use. Where the satellite is one of the most important technological developments in the field of communications in the nineties and the ads in various forms and functions one of the contents provided by satellite channels where these channels are keen to direct their messages in particular and communication, in general, to address a certain audience and convince and influence in order to achieve certain purposes of the source Or the body from which it originates, especially those that result in an in
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Abstract The wavelet shrink estimator is an attractive technique when estimating the nonparametric regression functions, but it is very sensitive in the case of a correlation in errors. In this research, a polynomial model of low degree was used for the purpose of addressing the boundary problem in the wavelet reduction in addition to using flexible threshold values in the case of Correlation in errors as it deals with those transactions at each level separately, unlike the comprehensive threshold values that deal with all levels simultaneously, as (Visushrink) methods, (False Discovery Rate) method, (Improvement Thresholding) and (Sureshrink method), as the study was conducted on real monthly data represented in the rates of theft crimes f
... Show MoreIn this study, a bioadhesive dosage form of eoconazole nitrate for vaginal delivery was designed using a combination of bioadhesive polymers: Carbopol 941 p and sodium carboxymethylcellulose or methylcellulose in different ratios. The bioadhesive strength was evaluated by measuring the force required to detach the tablet from sheep vaginal mucosal membrane. It was found that the bioadhesive force was directly proportional to Carbopol 941 p content in the different formulae. The formulae were tested for their swelling behavior using agar gel plate method. The results showed that formulae containing a combination of Carbopol 941 p and sodium carboxymethylcellulose had greater swelling index
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In this paper new methods were presented based on technique of differences which is the difference- based modified jackknifed generalized ridge regression estimator(DMJGR) and difference-based generalized jackknifed ridge regression estimator(DGJR), in estimating the parameters of linear part of the partially linear model. As for the nonlinear part represented by the nonparametric function, it was estimated using Nadaraya Watson smoother. The partially linear model was compared using these proposed methods with other estimators based on differencing technique through the MSE comparison criterion in simulation study.
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