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

Coated sand (CS) filter media was investigated to remove phenol and 4-nitrophenol from aqueous solutions in batch experiments. Local sand was subjected to surface modification as impregnated with iron. The influence of process variables represented by solution pH value, contact time, initial concentration and adsorbent dosage on removal efficiency of phenol and 4-nitrophenol onto CS was studied. Batch studies were performed to evaluate the adsorption process, and it was found that the Langmuir isotherm effectively fits the experimental data for the adsorbates better than the Freundlich model with the CS highest adsorption capacity of 0.45 mg/g for 4-nitrophenol and 0.25 mg/g for phenol. The CS was found to adsorb 85% of 4-nitrophenol and

In the present work, the critical micelle concentration (CMC) of the solution of Sodium dodecyl sulfate (SDS) as anionic surfactant, Cocamidopropyl Betaine (CAPB) as amphoteric surfactant, and their mixture have been determined using surface tension and conductivity measurements at a temperature range 293 -323 K. The adsorption and thermodynamic micellization parameters (?G?m, ?G?ads, ?max ,Amin,?cmc ) for individual surfactants was calculated. Rosen model which is focuses on the adsorbed mixed surfactant film at the air/solution interface was used to calculate the interaction parameter ( ?? ) at the interface and the activity coefficients g1 and g2. The results indicate that the CMC of the individual surfactants was affected by

This study was carried out in order to determine the toxic, mutagenic and antimutagenic effects for Mallow (Malva parviflora) in comparison to its mutagenic effect of Ultraviolet (UV) because it is consider physical mutagen by using parameters for the extract pri , with , post UV exposure by using bacterial system (G-system). The used system consisted of three isolates G3 Bacillus spp., G12 Arthrobacter spp. and G27 Brevibacterium spp.. The study depended on recording survival fraction (Sx) for studying the effects and induction of Streptomycin and Refampicin resistance mutants as a genetic markers.Water Extract was prepared from fresh and dry mallow leaves, stems, flowers and roots, in optimum concentration equal to (125µg/ml) which is

We propose a new method for detecting the abnormality in cerebral tissues present within Magnetic Resonance Images (MRI). Present classifier is comprised of cerebral tissue extraction, image division into angular and distance span vectors, acquirement of four features for each portion and classification to ascertain the abnormality location. The threshold value and region of interest are discerned using operator input and Otsu algorithm. Novel brain slices image division is introduced via angular and distance span vectors of sizes 24˚ with 15 pixels. Rotation invariance of the angular span vector is determined. An automatic image categorization into normal and abnormal brain tissues is performed using Support Vector Machine (SVM). St