Optimization of wear and friction characteristics of Phyllanthus Emblica seed oil based lubricant using response surface methodology

The escalating prices, rapid diminution of fossil fuels, tenacious regulations of the authorities, etc. enforced towards the alternate biogenic fuel for lubrication. The present study assessed the lubricity characteristics of Phyllanthus Emblica seed oil based lubricants by using a pin on disc (POD) tester. The design of experimentations has been carried out using response surface methodology (RSM). The value of parameters such as blend ratio, load and sliding speed ranges from 0 to 20%, 50 to 100?N and 1.3 to 3.8?m/s, respectively, are used to assess the value of specific wear rate (SWR) and coefficient of friction (COF). Test results illustrate that the adhesive wear occurred during the experiments. It has been observed that AB10 shows the probable results in terms of wear and friction characteristics as compared to other lubricant variants at low load and high sliding velocity conditions and perform as an excellent lubricant additive. This contributes towards the replacement of petroleum based lubricants. Analytical ferrography and total acid number (TAN) analysis of the used oil was also done to study the wear debris in the oil.     

Denoising Medical Images Using Deep Learning in IoT Environment

Medical Resonance Imaging (MRI) is a noninvasive, nonradioactive, and meticulous diagnostic modality capability in the field of medical imaging. However, the efficiency of MR image reconstruction is affected by its bulky image sets and slow process implementation. Therefore, to obtain a high-quality reconstructed image we presented a sparse aware noise removal technique that uses convolution neural network (SANR_CNN) for eliminating noise and improving the MR image reconstruction quality. The proposed noise removal or denoising technique adopts a fast CNN architecture that aids in training larger datasets with improved quality, and SARN algorithm is used for building a dictionary learning technique for denoising large image datasets. The proposed SANR_CNN model also preserves the details and edges in the image during reconstruction. An experiment was conducted to analyze the performance of SANR_CNN in a few existing models in regard with peak signal-to-noise ratio (PSNR), structural similarity index (SSIM), and mean squared error (MSE). The proposed SANR_CNN model achieved higher PSNR, SSIM, and MSE efficiency than the other noise removal techniques. The proposed architecture also provides transmission of these denoised medical images through secured IoT architecture.     

On the Microstructure and Wear Behavior of Fe–xCr–4Mn–3C Hardfacing Alloys

The present paper describes an investigation aimed at evaluating the microstructural and dry sliding adhesive wear characteristics of Fe–xCr–4Mn–3C hardfacing alloys applied through shielded metal arc welding. The effect of chromium addition on the microstructure of hardfacings was carried out by using optical microscope, field emission scanning electron microscope and X-ray mapping. Dry sliding wear tests were performed on a pin-on-disc wear tribometer. From the experimental results, it was observed that the primary carbides were refined and increased with the increase of chromium content. The morphology of carbides revealed that the primary carbides were rod shaped. The increased chromium content was also found to be beneficial to enhance hardness and wear resistance of hardfacings. The correlation between hardness and wear resistance exhibited the reliability of hardness as an indicator of the wear performance of hardfacings.     

Effect of Processing Variables on WC Nanoparticles Synthesized by Solvothermal Route

In this work, the effect of processing variables on the synthesis of WC nanoparticles by solvothermal route has been reported. Nanoparticles of tungsten carbide (WC) have been prepared by taking metallic magnesium (Mg), acetone (C₃H₆O), and tungsten trioxide (WO₃) in an autoclave at 600°C. The XRD results showed that the optimization of the reaction time facilitates the reduction as well as carburization of the tungsten source. The Williamson-–Hall analysis was used to study the effect of synthesis time on the crystallite size and lattice strain of the sample. Differential thermal analysis/thermogravimetric analysis shows the stability of the synthesized product. It has been observed that the synthesis of WC nanoparticles is a multistep process and the complete carburization reaction occurs at particular carburization time.     

An application-driven study of parallel system overheads andnetwork bandwidth requirements

Evaluating and analyzing the performance of a parallel application on an architecture to explain the disparity between projected and delivered performance is an important aspect of parallel systems research. However, conducting such a study is hard due to the vast design space of these systems. We study two important aspects related to the performance of parallel applications on shared memory parallel architectures. First, we quantify overheads observed during the execution of these applications on three different simulated architectures. We next use these results to synthesize the bandwidth requirements for the applications with respect to different network topologies. This study is performed using an execution-driven simulation tool called SPASM, which provides a way of isolating and quantifying the different parallel system overheads in a nonintrusive manner. The first exercise shows that in shared memory machines with private caches, as long as the applications are well-structured to exploit locality, the key determinant that impacts performance is network connection. The second exercise quantifies the network bandwidth needed to minimize the effect of network connection. Specifically, it is shown that for the applications considered, as long as the problem sizes are increased commensurate with the system size, current network technologies supporting 200-300 MBytes/sec link bandwidth are sufficient to keep the network overheads (such as latency and contention) within acceptable bounds     

Effect of Zinc-Ion on Indomethacin Degradation in Alkaline Aqueous Solutions

Kinetic studies have revealed that indomethacin degradation in the presence or absence of zincion at different temperatures in alkaline aqueous solutions followed an apparent firstorder rate constants. The rate constant-hydroxideion concentration profile was linearj _with a positive slope, suggesting the following rate lawt: k _obs = k₁ [OH]. There was no significant difference in activation energy and other parameter values calculated for indomethacin degradation in the presence or absence of zincion. Hence, zincion was found to have no effect on its degradation.     

The kinetics of Langmuir–Blodgett ZnO nano-film deposition for sensing electrodes

The kinetics of the monolayer formation of zinc oxide nanoparticles on water subphase was studied at different sample concentrations and barrier speeds. The recorded isotherms indicate that stearic acid can act as a suitable microenvironment for the deposition of zinc oxide when the spreading solution contains ~ 50% sample. The AFM image of the double layer shows that the film is nearly homogeneous with average thickness ~ 15 nm. The sensing ability of the nano-films was studied by cyclic voltammetry using ITO substrates, coated with zinc oxide nanoparticles as working electrode. It gave different reduction peaks for different pH electrolytes.     

Realization of task-based designs involving DH parameters: a modular approach

Task-based designs—proven to be successful for constrained environments—may face challenges at prototype development phase. To assist in generalized design and development of task-based serial manipulators for cluttered environments, a parameters-based modular approach is proposed. First, a task-based design strategy for serial manipulators is exhibited, using all the robotic parameters (DH parameters) as variables. The flexibility in robotic parameters enhances the possibility of good designs even for highly cluttered workspaces, but the realization of the resulting complicated designs is challenging. This work is an attempt to develop modular manipulators in correspondence to the task-based designs. The DH parameters-based proposed link modules, with reconfigurable architecture, can be adjusted and assembled to acquire the serial manipulators with designed robotic parameters. To validate the concept, some standardized 3R-configurations have been modelled using the proposed link modules. Case studies are presented on task-based design of robotic manipulators, with six and eight degrees of freedom, for service applications in realistic environments. The selected case studies include the robot design processes for applications of cleaning solar panels, and for the maintenance of the nuclear plants.