Many objective optimizations (MaOO) algorithms that intends to solve problems with many objectives (MaOP) (i.e., the problem with more than three objectives) are widely used in various areas such as industrial manufacturing, transportation, sustainability, and even in the medical sector.  Various approaches of MaOO algorithms are available and employed to handle different MaOP cases. In contrast, the performance of the MaOO algorithms assesses based on the balance between the convergence and diversity of the non-dominated solutions measured using different evaluation criteria of the quality performance indicators. Although many evaluation criteria are available, yet most of the evaluation and benchmarking of the MaOO with state-of-art a

Reverse Osmosis (RO) has already proved its worth as an efficient treatment method in chemical and environmental engineering applications. Various successful RO attempts for the rejection of organic and highly toxic pollutants from wastewater can be found in the literature over the last decade. Dimethylphenol is classified as a high-toxic organic compound found ubiquitously in wastewater. It poses a real threat to humans and the environment even at low concentration. In this paper, a model based framework was developed for the simulation and optimisation of RO process for the removal of dimethylphenol from wastewater. We incorporated our earlier developed and validated process model into the Species Conserving Genetic Algorithm (SCG

Drilling deviated wells is a frequently used approach in the oil and gas industry to increase the productivity of wells in reservoirs with a small thickness. Drilling these wells has been a challenge due to the low rate of penetration (ROP) and severe wellbore instability issues. The objective of this research is to reach a better drilling performance by reducing drilling time and increasing wellbore stability.

In this work, the first step was to develop a model that predicts the ROP for deviated wells by applying Artificial Neural Networks (ANNs). In the modeling, azimuth (AZI) and inclination (INC) of the wellbore trajectory, controllable drilling parameters, unconfined compressive strength (UCS), formation

Drilling deviated wells is a frequently used approach in the oil and gas industry to increase the productivity of wells in reservoirs with a small thickness. Drilling these wells has been a challenge due to the low rate of penetration (ROP) and severe wellbore instability issues. The objective of this research is to reach a better drilling performance by reducing drilling time and increasing wellbore stability.

In this work, the first step was to develop a model that predicts the ROP for deviated wells by applying Artificial Neural Networks (ANNs). In the modeling, azimuth (AZI) and inclination (INC) of the wellbore trajectory, controllable drilling parameters, unconfined compressive strength (UCS), formation

       The study aimed to determine the extent of market knowledge in the companies researched, as if market knowledge is qualified to lead the companies researched to achieve marketing performance , for this purpose, formulated hypotheses of the study in three hypotheses, the first major hypothesis "there is a correlation with significance of market knowledge to improve the marketing performance  , "while the second major hypothesis, "there is a significant moral influence of market knowledge to improve the marketing performance  " these hypotheses targeting to determine the role played by market knowledge in the leadership of companies researched to achieve improvement in marketing perfor

A substantial matter to confidential messages' interchange through the internet is transmission of information safely. For example, digital products' consumers and producers are keen for knowing those products are genuine and must be distinguished from worthless products. Encryption's science can be defined as the technique to embed the data in an images file, audio or videos in a style which should be met the safety requirements. Steganography is a portion of data concealment science that aiming to be reached a coveted security scale in the interchange of private not clear commercial and military data. This research offers a novel technique for steganography based on hiding data inside the clusters that resulted from fuzzy clustering. T

Most recent studies have focused on using modern intelligent techniques spatially, such as those
developed in the Intruder Detection Module (IDS). Such techniques have been built based on modern
artificial intelligence-based modules. Those modules act like a human brain. Thus, they should have had the
ability to learn and recognize what they had learned. The importance of developing such systems came after
the requests of customers and establishments to preserve their properties and avoid intruders’ damage. This
would be provided by an intelligent module that ensures the correct alarm. Thus, an interior visual intruder
detection module depending on Multi-Connect Architecture Associative Memory (MCA)

The physical substance at high energy level with specific circumstances; tend to behave harsh and complicated, meanwhile, sustaining equilibrium or non-equilibrium thermodynamic of the system. Measurement of the temperature by ordinary techniques in these cases is not applicable at all. Likewise, there is a need to apply mathematical models in numerous critical applications to measure the temperature accurately at an atomic level of the matter. Those mathematical models follow statistical rules with different distribution approaches of quantities energy of the system. However, these approaches have functional effects at microscopic and macroscopic levels of that system. Therefore, this research study represents an innovative of a wi

Abstract In this study, an investigation is conducted to realise the possibility of organic materials use in radio frequency (RF) electronics for RF-energy harvesting. Iraqi palm tree remnants mixed with nickel oxide nanoparticles hosted in polyethylene, INP substrates, is proposed for this study. Moreover, a metamaterial (MTM) antenna is printed on the created INP substrate of 0.8 mm thickness using silver nanoparticles conductive ink. The fabricated antenna performances are instigated numerically than validated experimentally in terms of S11 spectra and radiation patterns. It is found that the proposed antenna shows an ultra-wide band matching bandwidth to cover the frequencies from 2.4 to 10 GHz with bore-sight gain variation from 2.2 to