This study is concerned with the evaluation of the effect of Euphrates River water quality in Al-Samawa region during
the period 1984-2003 on efficiency and reliability of reverse osmosis desalination systems by calculating the calcium
sulfate scaling index depending on the following indicators: - TDS, Ca+2, Mg+2, Na+1, Cl-1, So4-2, HCO3-1. It was
found from data analysis that this index for these units is greater than permissible limit. Also, the fitted relationship
between this index and TDS is logarithmic, i.e. this index varies more rapidly than TDS, and consequently it is more
representative to the water quality than TDS.

The growing interest in the use of chaotic techniques for enabling secure communication in recent years has been motivated by the emergence of a number of wireless services which require the service provider to provide low bit error rates (BER) along with information security. This paper investigates the feasibility of using chaotic communications over Multiple-Input-Multiple-Output (MIMO) channels. While the use of Chaotic maps can enhance security, it is seen that the overall BER performance gets degraded when compared to conventional communication schemes. In order to overcome this limitation, we have proposed the use of a combination of Chaotic modulation and Alamouti Space Time Block Code. The performance of Chaos Shift Keying (CSK) wi

The Combined Economic Emission Dispatch (CEED) problem is crucial for optimizing power system operation by minimizing costs and emissions while ensuring grid stability and meeting demand. This paper addresses the complex, nonlinear, and nonconvex nature of CEED, arising from factors like valve-point effects and transmission losses, which necessitates efficient metaheuristic algorithms. We introduce an Improved Zebra Optimization Algorithm (IMZOA), an enhanced bio-inspired technique integrating advanced adaptive foraging and dynamic defense mechanisms, along with a cubic function for CEED modeling, to improve search efficiency and convergence. IMZOA demonstrates significant numerical improvements, achieving up to a 0.80 % cost reduction for

Background Due to the intermittent, nonlinear, and uncertain behavior of renewable energy sources (res) such as solar and wind, grid stability and reliability require very high forecasting and optimization skills as widely reported in the literature. Traditional optimization methods work very well in small or static systems but are suffer difficulty on large-scale, dynamic and stochastic renewable environment due to their NP-hard nature. Methods The framework introduces the concept of a Machine Learning-Assisted Hybrid Cuckoo Search (ML-HCS) that combines CS with a hybrid metaheuristic and integrates Long Short-Term Memory (LSTM) networks for forecasting based on both regression models of LSTMs and hybrid optimization algorithm

   There is a growing imperative to extract oil not only through primary and secondary means but also via tertiary recovery methods to meet the escalating global energy demands. Consequently, Enhanced Oil Recovery (EOR) is slated to increase significance in the oil industry in the coming years. The amalgamation of low salinity water (LSW) with chemicals to augment oil recovery has gained substantial traction in recent years owing to its demonstrated effectiveness. In this study, a systematic investigation utilizing contact angle measurements to elucidate the underlying mechanisms was undertaken. The results reveal that the contact angle (CA) demonstrated the effectiveness of the combined fluid in altering the wettability from oil-