Sludge from stone-cutting (SSC) factories and stone mines cannot be used as decorative stones, stone powder, etc. These substances are left in the environment and cause environmental problems. This study aim is to produce artificial stone composite (ASC) using sludge from stone cutting factories, cement, unsaturated resin, water, silicon carbide nanoparticles (SiC-NPs), and nano-graphene oxide (NGO) as fillers. Nano graphene oxide has a hydrophobic plate structure that water is not absorbed due to the lack of surface tension on these plates. NGO has a significant effect on the properties of artificial stone due to its high specific surface area and low density in the composite. Its uniform distribution in ASC is very low due to its hydrophobicity, which can be modified by using unsaturated resin and silicon carbide nanoparticles (SiC-NPs). The obtained results show a remarkable increase and improvement in the mechanical properties of the artificial stone composite in the samples containing modified NGO with SiC-NPs. These samples have less porosity, smoother, more polished surface and, high bending and compressive strength. The addition of these materials to the artificial stone has increased durability and reduced costs and has caused water repellency, and prevented the penetration of harmful ions such as chloride, etc.
More than 95% of the industrial controllers in use today are PID or modified PID controllers. However, the PID is manually tuning to be responsive so that the Process Variable is rapidly and steady moved to track the set point with minimize overshoot and stable output. The paper presents generic teal-time PID controller architecture. The developed architecture is based on the adaption of each of the three controller parameters (PID) to be self- learning using individual least mean square algorithm (LMS). The adaptive PID is verified and compared with the classical PID. The rapid realization of the adaptive PID architecture allows the readily fabrication into a hardware version either ASIC or reconfigurable.
The research aims to study the corrosion of aluminum alloy(6061) in 0.6 mol. dm-3 NaCl solution in base medium was examined with out and with Gallic acid as environmentally – friendly corrosion inhibitor at temperature range (298-313)K. The inhibitive action of gallic acid on corrosion of aluminum alloy(6061) in KOH solution was examined through electrochemical polarization method using potentiostatic technique and surface analysis by optical microscopy, Polarization measurements indicate that the examined compound act as a mixed type inhibitor. Results appeared that the inhibition occurs through adsorption of the inhibitor molecules on the metal surface and it was obeyed
... Show MoreCorrosion behavior of aluminium in 0.6 mol. dm-3 NaCL solution in acidic medium ( ) was investigated in the absence and presence of different concentrations of amino acid, glutamic acid, as environmentally – friendly corrosion inhibitor over temperature range (293-308)K. The investigation involved electrochemical polarization method using potentiostatic technique and optical microscopy, the inhibition efficiency increased with an increase in inhibitor concentration but decreased with increase in temperature. Results showed that the inhibition occurs through adsorption of the inhibitor molecules on the metal surface and it was found to obey Langmuir adsorption isotherm. Some thermodynamic paramet
... Show MoreThe COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system
... Show MoreBackground: With the increasing demands for adult orthodontics, a growing need arises to bond attachments to porcelain surfaces. Optimal adhesion to porcelain surface should allow orthodontic treatment without bond failure but not jeopardize porcelain integrity after debonding.The present study was carried out to compare the shear bond strength of metal bracket bonded to porcelain surface prepared by two mechanical treatments and by using different etching systems (Hydrofluoric acid 9% and acidulated phosphate fluoride 1.23%). Materials and Methods: The samples were comprised of 60 models (28mm *15mm*28mm) of metal fused to porcelain (feldspathic porcelain). They were divided as the following: group I (control): the porcelain surface left u
... Show MoreThe objective of drilling parameters optimization in Majnoon oilfield is to arrive for a methodology that considers the past drilling data for five directional wells at 35 degree of inclination as a baseline for new wells to be drilled. Also, to predicts drilling performance by selecting the applied drilling parameters generated the highest rate of penetration (ROP) at each section. The focal point of the optimization process is to reduce drilling time and associated cost per each well. The results of this study show that the maximum ROP could not be achieved without sufficient flow rate to cool and clean the bit in clay intervals (36" and 24") hole sections. Although the influence of combination of Weight on Bit (WOB), Round per minute
... Show MoreThe issue of image captioning, which comprises automatic text generation to understand an image’s visual information, has become feasible with the developments in object recognition and image classification. Deep learning has received much interest from the scientific community and can be very useful in real-world applications. The proposed image captioning approach involves the use of Convolution Neural Network (CNN) pre-trained models combined with Long Short Term Memory (LSTM) to generate image captions. The process includes two stages. The first stage entails training the CNN-LSTM models using baseline hyper-parameters and the second stage encompasses training CNN-LSTM models by optimizing and adjusting the hyper-parameters of
... Show MoreThe goal of this work is to study plasma parameters for Fe plasma generated by exploding wire (EEW) in carbon nanotubes-water colloid with three current values (50, 100 and 150)A. In this research, the plasma electron temperature (Te), the electron density (ne), electron density (ne), plasma frequency(f p), Debye length (λD) and Debye number (ND) were found for Fe produced by Arc discharge plasma. Boltzmann plot was used to calculate the plasma electron temperature (Te);electron density (ne) was calculated from Stark broadening. It was found that the electron temperature values increased from (0.4
... Show MoreTwo different polyvinyl alcohol/polyvinyl chloride (PVA/PVC) hollow fiber composite nanofiltration membranes were prepared after PVC hollow fiber membranes were coated using dip-coating method with PVA aqueous solution, which was composed of PVA, fatty alcohol polyoxyethylene ether (AEO9), and water [PVA/AEO9/water (4:0.5:95.5) wt%]. Effect of two different PVC hollow fiber immersion times in coating solution were studied. Cross-section, internal and external surfaces of the PVC hollow fibers and PVA/PVC composite nanofiltration membranes structures were characterized by scanning electron microscopy (SEM), pure water permeation flux and solutes rejection. It was found that, the coating layer thickness on the outer surface of the 19 wt% P
... Show More