Industrial wastewater containing nickel, lead, and copper can be produced by many industries. The reverse osmosis (RO) membrane technologies are very efficient for the treatment of industrial wastewater containing nickel, lead, and copper ions to reduce water consumption and preserving the environment. Synthetic industrial wastewater samples containing Ni(II), Pb(II), and Cu(II) ions at various concentrations (50 to 200 ppm), pressures (1 to 4 bar), temperatures (10 to 40 ^oC), pH (2 to 5.5), and flow rates (10 to 40 L/hr), were prepared and subjected to treatment by RO system in the laboratory. The results showed that high removal efficiency of the heavy metals could be achieved by RO process (98.5%, 97.5% and 96% for Ni(II),

Many of mechanical systems are exposed to undesired vibrations, so designing an active vibration control (AVC) system is important in engineering decisions to reduce this vibration. Smart structure technology is used for vibration reduction. Therefore, the cantilever beam is embedded by a piezoelectric (PZT) as an actuator. The optimal LQR controller is designed that reduce the vibration of the smart beam by using a PZT element.  

In this study the main part is to change the length of the aluminum cantilever beam, so keep the control gains, the excitation, the actuation voltage, and mechanical properties of the aluminum beam for each length of the smart cantilever beam and observe the behavior and effec

Terrestrial isopods play an important role in the biodegradation of many wastes which gives agreat importance in the nutrient cycles and ecosystem services , therefore this paper aims to use species Orthodillo chiltoni (Vandel, 1973) as a model organism in bioremediation of urban environment with municipal wastes, agricultural fields, parks and markets wastes. Samples of these wastes included potato peels, orange fruit leaves, thyme plant and sawdust,cardboard residues , the experiments were carried out in laboratory condition similar to the living environment of this species in terms of temperature, humidity and intensity lighting. The applied results have shown that

    Multivariate Non-Parametric control charts were used to monitoring the data that generated by using the simulation, whether they are within control limits or not. Since that non-parametric methods do not require any assumptions about the distribution of the data.  This research aims to apply the multivariate non-parametric quality control methods, which are Multivariate Wilcoxon Signed-Rank ( ) , kernel principal component analysis (KPCA) and k-nearest neighbor ( −

Background/Objectives: The purpose of this study was to classify Alzheimer’s disease (AD) patients from Normal Control (NC) patients using Magnetic Resonance Imaging (MRI). Methods/Statistical analysis: The performance evolution is carried out for 346 MR images from Alzheimer's Neuroimaging Initiative (ADNI) dataset. The classifier Deep Belief Network (DBN) is used for the function of classification. The network is trained using a sample training set, and the weights produced are then used to check the system's recognition capability. Findings: As a result, this paper presented a novel method of automated classification system for AD determination. The suggested method offers good performance of the experiments carried out show that the

There are many images you need to large Khoznah space With the continued evolution of storage technology for computers, there is a need nailed required to reduce Alkhoznip space for pictures and image compression in a good way, the conversion method Alamueja

Image segmentation can be defined as a cutting or segmenting process of the digital image into many useful points which are called segmentation, that includes image elements contribute with certain attributes different form Pixel that constitute other parts. Two phases were followed in image processing by the researcher in this paper. At the beginning, pre-processing image on images was made before the segmentation process through statistical confidence intervals that can be used for estimate of unknown remarks suggested by Acho & Buenestado in 2018. Then, the second phase includes image segmentation process by using "Bernsen's Thresholding Technique" in the first phase. The researcher drew a conclusion that in case of utilizing

Large quantities of contaminated carwash wastewater are produced per day from carwash places. Extensively it contains large quantities of chemicals from detergents, oil, grease, heavy metals, suspended solids, types of hydrocarbons, and biological contents. A novel electrocoagulation treatment by foil electrodes was conducted to remove COD, turbidity, Total Dissolved Solids (TDS) from contaminated carwash wastewater and decrease its Electrical Conductivity (EC). A thin layer of aluminum foil is used as an electrode in this treatment process. The effects of different voltage and treatment times were studied. The best result was found at a voltage of 30 volts and treatment time 90 minute where the removal efficiency of COD