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 coefficien

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 correlat

In this paper, we investigate the automatic recognition of emotion in text. We perform experiments with a new method of classification based on the PPM character-based text compression scheme. These experiments involve both coarse-grained classification (whether a text is emotional or not) and also fine-grained classification such as recognising Ekman’s six basic emotions (Anger, Disgust, Fear, Happiness, Sadness, Surprise). Experimental results with three datasets show that the new method significantly outperforms the traditional word-based text classification methods. The results show that the PPM compression based classification method is able to distinguish between emotional and nonemotional text with high accuracy, between texts invo

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

In this study, genetic algorithm was used to predict the reaction kinetics of Iraqi heavy naphtha catalytic reforming process located in Al-Doura refinery in Baghdad.  One-dimensional steady state model was derived to describe commercial catalytic reforming unit consisting of four catalytic reforming reactors in series process.

The experimental information (Reformate composition and output temperature) for each four reactors collected at different operating conditions was used to predict the parameters of the proposed kinetic model. The kinetic model involving 24 components, 1 to 11 carbon atoms for paraffins and 6 to 11 carbon atom for naphthenes and aromatics with 71 reactions. The pre-exponential Arrhenius constants and a

Based on the results of standard penetration tests (SPTs) conducted in Al-Basrah governorate, this research aims to present thematic maps and equations for estimating the bearing capacity of driven piles having several lengths. The work includes drilling 135 boreholes to a depth of 10 m below the existing ground level and three standard penetration tests (SPT) at depths of 1.5, 6, and 9.5 m were conducted in each borehole. MATLAB software and corrected SPT values were used to determine the bearing capacity of driven piles in Al-Basrah. Several-order interpolation polynomials are suggested to estimate the bearing capacity of driven piles, but the first-order polynomial is considered the most straightforward. Furthermore, the root means squar

Surgical site infections are the second most common type of adverse events occurring in hospitalized patients. Surgical antibiotic prophylaxis refers to the use of preoperative and postoperative antibiotics to decrease the incidence of postoperative wound infections. The objective of this study was to evaluate the antibiotic administration pattern for surgical antibiotic prophylaxis and the adherence to American Society of Health-System Pharmacists surgical antibiotic prophylaxis guideline in Medical City Teaching Hospitals/Baghdad. The medical records of one hundred patients who underwent elective surgical procedures were reviewed. Adherence to the recommendations of American society of health‑system pharmacists guideline was ass

This study dealt with the basics of financial inclusion in terms of concept, importance and objectives, The empowerment of women financially and bank ,and then the relationship between financial inclusion and women, and determine the requirements of inclusion Financial resources for women. The analytical descriptive method was used for data, which included reviewing and analyzing information and data in economic and financial literature. The study: reached a number of conclusions, the most important of which are Financial inclusion contributes to women's financial and banking support, as there is a positive relationship between financial institutions Banking and women's access to financial and banking services, thus playing a rol

Perchloroethylene (PERC) is commonly used as a dry-cleaning solvent, it is attributed to many deleterious effects in the biological system. The study aimed to investigate the harmful effect associated with PERC exposure among dry-cleaning workers. The study was carried out on 58 adults in two groups. PERC-exposed group; include thirty-two male dry-cleaning workers using PERC as a dry-cleaning solvent and twenty-six healthy non-exposed subjects. History of PERC exposure, use of personal protection equipment (PPE), safety measurement of the exposed group was recorded. Blood sample was taken from each participant for measurement of hematological markers, liver and kidney function tests. The results showed that 28.1% of the workers were usin