The prediction process of time series for some time-related phenomena, in particular, the autoregressive integrated moving average(ARIMA) models is one of the important topics in the theory of time series analysis in the applied statistics. Perhaps its importance lies in the basic stages in analyzing of the structure or modeling and the conditions that must be provided in the stochastic process. This paper deals with two methods of predicting the first was a special case of autoregressive integrated moving average which is ARIMA (0,1,1) if the value of the parameter equal to zero, then it is called Random Walk model, the second was the exponential weighted moving average (EWMA). It was implemented in the data of the monthly traff

This study examined the effects of water scarcity on rural household economy in El Fashir Rural Council / North Darfur State- western Sudan. Both quantitative and qualitative methods were used as to get a deeper understanding of the impact of water scarcity on the rural house economy in the study area. 174 households out of 2017 were selected from 45 villages which were distributed in eight village councils forming the study area. Statistical methods were used to manipulate the data of the study. The obtained results revealed that water scarcity negatively affected the rural household economy in the study area in many features. These include the followings: much family efforts and time were directed to fetch for water consequentl

In this study, we fabricated nanofiltration membranes using the electrospinning technique, employing pure PAN and a mixed matrix of PAN/HPMC. The PAN nanofibrous membranes with a concentration of 13wt% were prepared and blended with different concentrations of HPMC in the solvent N, N-Dimethylformamide (DMF). We conducted a comprehensive analysis of these membranes' surface morphology, chemical composition, wettability, and porosity and compared the results. The findings indicated that the inclusion of HPMC in the PAN membranes led to a reduction in surface porosity and fiber size. The contact angle decreased, indicating increased surface hydrophilicity, which can enhance flux and reduce fouling tendencies. Subsequently, we evaluated the e

Formation of emulsions during oil production is a costly problem, and decreased water content in emulsions leads to increases productivity and reduces the potential for pipeline corrosion and equipment used. The chemical demulsification process of crude oil emulsions is one of the methods used for reducing water content. The demulsifier presence causes the film layer between water droplets and the crude oil emulsion that to become unstable, leading to the accelerated of water coalescence. This research was performed to study the performance of a chemical demulsifier Chimec2439 (commercial) a blend of non-ionic oil-soluble surfactants. The crude oils used in these experiments were Basrah and Kirkuk Iraqi crude oil. These

This work presents an investigation on the fabrication and characterization of Fe doped zeolitic imidazolate framework (ZIF-8) of 1:1 M ratio of Zn:Fe (Fe/Zn-ZIF-8) and adsorption performances of acquired materials. The synthesized Zn-ZIF-8, Fe-ZIF-8, and Fe/Zn-ZIF-8 materials were characterized for the phase structure, morphology, elemental analysis and surface area by using X-ray diffraction (XRD), Field emission scanning electron microscope (FESEM), Energy Dispersive X-Ray (EDX), and BET surface area, respectively. The results revealed the adsorption capacity was enhanced by incorporation of Fe into ZIF-8 structure. The CR dye adsorption capacities were 287, 219, and 412 mg/g for Zn-ZIF-8, Fe-ZIF-8, and Fe/Zn-ZIF-8 adsorbers, respectivel

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In this study, multi-objective optimization of nanofluid aluminum oxide in a mixture of water and ethylene glycol (40:60) is studied. In order to reduce viscosity and increase thermal conductivity of nanofluids, NSGA-II algorithm is used to alter the temperature and volume fraction of nanoparticles. Neural network modeling of experimental data is used to obtain the values of viscosity and thermal conductivity on temperature and volume fraction of nanoparticles. In order to evaluate the optimization objective functions, neural network optimization is connected to NSGA-II algorithm and at any time assessment of the fitness function, the neural network model is called. Finally, Pareto Front and the corresponding optimum points are provided and