A vortex tube silt ejector is a curative hydraulic structure used to remove sediment deposits from canals and is recognized as one of the most efficient substitutes for physically removing canal sediment. The spatiall...
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A vortex tube silt ejector is a curative hydraulic structure used to remove sediment deposits from canals and is recognized as one of the most efficient substitutes for physically removing canal sediment. The spatially varied flow in the channel and the rotational flow behavior in the tube make the silt removal process complex. It is even harder to accurately predict the silt removal efficiency by traditional models accurately. However, artificial intelligence(AI) and machine learning approaches have emerged as robust substitutes for studying complex processes. Therefore, this research makes use of AI approaches; support vector machine(SVM), random forest(RF), random tree(RT), and multivariate adaptive regression spline(MARS) to compute the vortex tube silt ejection efficiency using the laboratory data sets. The outcomes of the artificial intelligence(AI)-based techniques also were compared with traditional models. It was found that the RT model(root mean square error, RMSE = 2.165, Nash Sutcliffe efficiency, NSE = 0.98) outperforms the other applied approaches which had relatively more significant result errors. The sensitivity analysis of the process depicts the extraction ratio as the key parameter in the computation of vortex tube silt ejector removal efficiency. The findings of the AI-based approaches discussed in the current study might be helpful for hydraulic engineers as well as researchers in the assessment of the removal efficiency of vortex tube silt ejectors.
This article presents a dual-band switchable and tunable band-pass filter for Bluetooth and 5G NR applications. The filter functions at 2.41 GHz for Bluetooth and 3.55 GHz for 5G, utilizing independent switching and t...
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Approximate computing and reversible logic have become vital concepts in designing low-power, area-efficient datapath units for portable image and signal processing applications. In this approach, a low-power, reversi...
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Approximate computing and reversible logic have become vital concepts in designing low-power, area-efficient datapath units for portable image and signal processing applications. In this approach, a low-power, reversible architecture targeting digital image watermarking is proposed. The reported low-power Reversible Watermark Architecture (LP-RWA) implements a novel high-speed embed unit to blend the watermark image onto the cover image. The proposed embed unit performs block-level parallel accumulation and incorporates hybrid computing with approximate parallel carry logic (APC) for n/2 least significant bits (LSBs) and the standard carry logic (SC) for n/2 most significant bits (MSBs) to achieve area efficiency and speed improvement. Note that the implementation of APC in the least n/2 bits introduces a maximal error of 2n/2;however, we add a suitable constant unit bias at an appropriate position to faithfully restrict the error within -2n/2–1 to + 2n/2–1. Furthermore, we use reversible logic for implementation to achieve low-power operation and perfect recovery of the watermark image from the blended image without much signal loss. An area-efficient version of the LP-RWA (AE-RWA) is also reported, eliminating the generation of least significant n/4 bits in the approximate part of the Reversible Faithful Embed (RFE) unit. This elimination operation increases the average error during recovery;however, the maximum error is maintained within ± 2n/2–1. Evaluations show that LP-RWA exhibits 38.8%, 25%, 27.7%, and 27.2% reductions, and AE-RWA exhibits 46%, 32.7%, 34.3%, and 58.6% reductions in Quantum Cost (QC), Gate Count (GC), Garbage Output (GO), and Logic Depth, respectively, when compared to the standard reversible watermarking architecture. Synthesis results of LP-RWA and AE-RWA designs with 90 nm Application Specific Integrated Circuit (ASIC) Process Design Kit (PDK) technology with a number of bits in input operand (n) = 16 and employing 4 bits in each block sho
A non-invasive Internet of Things-based system using Photoplethysmography signals for early diabetes detection. Integration with cloud technology ensures real-time monitoring and user convenience. Achieves up to 90% a...
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Sodium alginate(SA)/chitosan(CH)polyelectrolyte scaffold is a suitable substrate for tissue-engineering *** present study deals with further improvement in the tensile strength and biological properties of this type o...
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Sodium alginate(SA)/chitosan(CH)polyelectrolyte scaffold is a suitable substrate for tissue-engineering *** present study deals with further improvement in the tensile strength and biological properties of this type of scaffold to make it a potential template for bone-tissue *** experimented with adding 0%–15%(volume fraction)gelatin(GE),a protein-based biopolymer known to promote cell adhesion,proliferation,and *** resulting tri-polymer complex was used as bioink to fabricate SA/CH/GEmatrices by three-dimensional(3D)*** studies using scanning electron microscopy revealed the microfibrous porous architecture of all the structures,which had a pore size range of 383–419μm.X-ray diffraction and Fourier-transform infrared spectroscopy analyses revealed the amorphous nature of the scaffold and the strong electrostatic interactions among the functional groups of the polymers,thereby forming polyelectrolyte complexes which were found to improve mechanical properties and structural *** scaffolds exhibited a desirable degradation rate,controlled swelling,and hydrophilic characteristics which are favorable for bone-tissue *** tensile strength improved from(386±15)to(693±15)kPa due to the increased stiffness of SA/CH scaffolds upon addition of *** enhanced protein adsorption and in vitro bioactivity(forming an apatite layer)confirmed the ability of the SA/CH/GE scaffold to offer higher cellular adhesion and a bone-like environment to cells during the process of tissue *** vitro biological evaluation including the MTT assay,confocal microscopy analysis,and alizarin red S assay showed a significant increase in cell attachment,cell viability,and cell proliferation,which further improved biomineralization over the scaffold *** addition,SA/CH containing 15%gelatin designated as SA/CH/GE15 showed superior performance to the other fabricated 3D structures,demonstrating its pote
The surface roughness of the material is playing an essential role in metal forming process. In recent days, research about surface roughness of the advanced alloys has been increased. The current research work is to ...
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Decentralized power generation using renewable gaseous biofuels faces challenges due to their inconsistent quality and availability. Mixing producer gas (PG) with diesel as a secondary fuel is a promising option, but ...
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The research aims to investigate the impact of GO and ZnO nanoparticles in a 20% mahua biodiesel blend (B20) on direct injection diesel engine performance. Mahua oil, selected for its non-edible source and local avail...
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The research aims to investigate the impact of GO and ZnO nanoparticles in a 20% mahua biodiesel blend (B20) on direct injection diesel engine performance. Mahua oil, selected for its non-edible source and local availability, provides a sustainable fuel option. To improve combustion and reduce emissions, nanoparticles are added. Artificial neural networks (ANNs) and response surface methodology (RSM) are then used to predict and optimize engine operating parameters, leveraging their ability to model intricate relationships and analyze experimental data, ultimately aiming to create a more efficient and environmentally friendly fuel system. At a concentration of 75 ppm, GO and ZnO nanoparticles were taken into consideration. Additionally, a dispersant (TWEEN 80) and surfactant (CTAB) were mixed respectively at a ratio of 1:1. Using a spectrophotometer, stability analysis was carried out on different nanofuel samples, and a study based on experiments was done on a diesel engine. The output factors examined are BSFC, BTE, NHRR, CP, UHC, CO, NOx, and smoke Opacity. These metrics were based on performance, combustion, and emission characteristics. Input parameters such as fuel samples, injection pressure, and engine load were considered. The injection pressure varied at 200, 225, and 250 bar, whereas the load was considered to be 5%, 50%, 75%, and 100%, respectively. When compared to other fuel samples, dispersant included GO and ZnO nanoparticles in B20 shown optimal results. The B20 + GO 75 ppm + TWEEN 80 75 ppm combination has shown a 5.293% decrease in BSFC and 5.067% improvement in BTE at 250 bars. Furthermore, significant improvements were observed in key combustion parameters, CP increased by 3.13%, and NHRR increased by a substantial 43.50%. CO, UHC, NOx, and smoke opacity were all reduced by around 11.07%, 37.63%, 27.77%, and 38.55% respectively. With R2 values consistently between 0.93 and 0.99, the ANN and RSM predictions demonstrate a perfect fit to the data,
The proposed underground tunnel for Mass Rapid Transit Line 1,Dhaka brings immense attention to the engineers and experts not only because of its construction challenges through a densely-built city,but also for the p...
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The proposed underground tunnel for Mass Rapid Transit Line 1,Dhaka brings immense attention to the engineers and experts not only because of its construction challenges through a densely-built city,but also for the potential tunneling-induced ground *** very preliminary study investigates the ground surface movement due to the progression of the tunnel boring machine(TBM)using numerical analysis.A series of finite element(FE)models have been developed using PLAXIS 3D,in which Mohr–Coulomb(MC),modified Cam-Clay(MCC),and hardening soil(HS)have been *** in-field data of Mashhad Metro Line-2 have been compared to verify PLAXIS 3D’s efficacy in tunnel ***,the outcomes of the FE analyses are compared with the existing empirical *** PLAXIS 3D analysis considering the MCC soil model exhibits strong agreement with the real monitored data,with a variance of only 3.85%.After simulating different stages of the tunnel construction,results are reported in terms of the distance of the inflexion point from the center,the settlement trough pattern,the maximum transverse settlements,and the vertical *** are also compared with the established empirical *** order to comprehend the surface settlement with various tunnel depths and diameters,a parameter dependency study has been carried *** analysis findings showed that increasing the TBM’s depth and radius causes the inflexion point’s distance from the center of the tunnel to increase by 4%and decrease by 5%,*** is also observed that as tunnel depth increases,the overall settlement of the tunnel lowers by 11%for every additional 5 meters of *** MCC model,out of the three,exhibits the most accurate value of the settlement compared to that obtained from the empirical solutions,and also the best-fit form to the Gaussian curve.
The effect of single-walled carbon nanotubes (SWCNTs) as fillers in polyurethane matrix composites on the efficiency of attenuating electromagnetic waves in the X-band region (8–12 GHz) was studied in the current wor...
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