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Effect of back pressure and temperature on the densification behaviour of Al-Mg alloy
No full textThe current research has been aimed to study densification of Al-Mg alloy which was made with optimum sized Nanopowders through Equal Channel Angular Pressing (ECAP) technique. Al-Mg alloy nanopowder was synthesized through high energy ball milling process in the optimised condition. XRD was used to analyze the crystallite sizes of powders prepared at 10, 20, 30, 40 and 50 hrs in ball mill and the minimum crystallite size of 20.388nm achieved at 30hrs was found to be the best
milling time. Consolidated specimens were prepared at three working conditions; without back pressure, with back pressure and with back pressure at high temperature (250°C). At each working condition, two passes were made to get better
densification in the specimen. The specimens were analyzed for hardness, density,and microstructure. It was found that 92.11% of dense material was formed with a hardness of 64HRB
Molecular docking and dynamic simulations for antiviral compounds against SARS-CoV-2: A computational study
No full textThe aim of this study was to develop an appropriate anti-viral drug against the SARS-CoV-2 virus. An immediately qualifying strategy would be to use existing powerful drugs from
various virus treatments. The strategy in virtual screening of antiviral databases for possible therapeutic effect would be to identify promising drug molecules, as there is currently no
vaccine or treatment approved against COVID-19. Targeting the main protease (pdb id: 6LU7) is gaining importance in anti-CoV drug design. In this conceptual context, an attempt
has been made to suggest an in silico computational relationship between US-FDA approved drugs, plant-derived natural drugs, and Coronavirus main protease (6LU7) protein. The evaluation of results was made based on Glide (Schrödinger) dock score. Out of 62 screened compounds, the best docking scores with the targets were found for compounds: lopinavir, amodiaquine, and theaflavin digallate (TFDG). Molecular dynamic (MD) simulation study was also performed for 20 ns to confirm the stability behaviour of the main protease and inhibitor complexes. The MD simulation study validated the stability of three compounds in the protein binding pocket as potent binders
Evaluating and ranking the Indian private sector banks—A multi‐criteria decision‐making approach
No full textThe paper examines the performance of Indian private sector banks based on various combinations of multi-criteria decision-making techniques. Annual reports of the respective banks were used to capture the data and measure the performance by considering multiple inputs and outputs. The data are analyzed through notable multiple criteria decision-making (MCDM) techniques, CRITIC, TOPSIS, and grey rela-tional analysis (GRA). The study reveals that HDFC is the best performing bank among other private sector banks and creates a benchmark. Applying the combination of MCDM techniques, namely CRITIC-TOPSIS and CRITIC-GRA, HDFC is ranked first followed by Bandhan Bank as the second. Other banks are ranked differently due to methodological differences. After obtaining the ranks by CRITIC-TOPSIS and CRITIC-GRA, the ranks are tested using the Wilcoxon signed-rank test. Only private sector banks are considered for the current study. Future studies on the performance of banks can be taken up by comparing different types of banks, targeting an extension of the time frame studied. The findings suggest that the private sector banks need to increase their performance by investing in income-generating areas. Improving the performance will help them in surviving in the market as well as competing with the top public sector and foreign banks. The findings can also be useful to various stakeholders and, in particular, to investors to know the value of the banks for future investments. For the first time, researchers have used a combination of MCDM techniques such as CRITIC-TOPSIS and CRITIC-GRA. Selected inputs and outputs have been studied for the private sector banks using MCDM techniques to measure the performance
Effective Ensemble Strategies for Predicting the Cardiac Diseases
Get PDFNumber of people losing their lives due to heart disease is growing day by day, revealing the need of a model which predicts beforehand. An initiative has to be taken to aid the people by giving them a cautionary advice about the disease at the correct time. It is not easy for everyone to afford expensive treatments and medications so there is urgency of a structure which can quickly go through the information of the patient and inform them at an earlier stage if they test positive. We need a logical process that analyzes and finds unrevealed data and figures in the medical data. Thus, we propose to perform the analysis of given dataset by performing the data validation and preprocessing techniques, exploration data analysis visualization and training a model, build a classification model and then performance measurements of supervised machine learning algorithms with evaluation classification report, identify the confusion matrix and categorizing data from priority. The main objective is to make a predictive analytics model to diagnose the various stages of heart patients by ensemble learning methods like Bagging, Boosting and Voting which aims to enhance the accuracy of the
deficient algorithms. Outcome of these ensemble techniques are analyzed and the one that proves to enhance the precision is considered and showcased using a GU
Modeling of glass fiber reinforced composites for optimal mechanical properties using teaching learning based optimization and artificial neural networks
No full textThe present work is aimed at determining mechanical properties of chopped strand glass fber reinforced composite
laminates manufactured based on the design of experiments by resin transfer molding at various injection pressures with
4, 5 and 6 layers. Response surface methodology was implemented to the experimental data for evaluating the efect
of number of layers and resin injection pressure on mechanical properties and void content. Teaching learning based
optimization (TLBO) has been proposed to predict optimal (maximum) mechanical properties of composite by optimizing the number of layers and injection pressure. Artifcial neural network (ANN) with feed forward back propagation algorithm was also used to predict the responses and compare with experimental and TLBO results. It was found that the predicted values of responses from TLBO and ANN are good in agreement with experimental result
Effect Of Various Solid Lubricants On Surface Quality In Turning Of Inconel 718
No full textMetal cutting or machining is a backbone of manufacturing industries. In machining process, heat is generated and it must be removed with the help of cutting fluid. Generally, hydrocarbon oil based cutting fluid is used, but it leads to
environmental pollution and as well as operator’s ill health. Solid lubrication is a good alternative to hydro carbon oil based cutting fluid. In this work, turning process is carried out on Inconel 718 with perpendicular direction textured cutting insert
filled with different solid lubricants. Solid lubricants as lubricant materials, which are basically solid but become soft due to frictional heat at the point of contact. In this work, Molybdenum disulfide (MoS2) and Graphite solid lubricants are used.
Experiments are performed as per L9 orthogonal array and the effect of each process parameter is determined through the Analysis of Variance (ANOVA). The result revealed that solid lubricant with textured tool produces a continuous lubricating
layer on the surface of the tool due to the thermal expansion of heat produced during machining. This thin layer may reduce friction in the machining zone. Perpendicular direction textured cutting inserts are used to reduce friction and good surface finish is obtained. Compared with MoS2, graphite has shown better results in terms of surface finish due to its low shear strength properties
Structural, morphological, optical and mechanical studies of annealed ZnO nano particles
No full textThe structural, morphological, optical and mechanical properties of Zinc oxide (ZnO) nanoparticles annealed at different temperatures from 500°C to 1000°C with a step
size of 1000C were synthesised from Sol-Gel method. The X-ray diffraction study revealed that ZnO has hexagonal Wurtzite structure. Scanning Electron Microscope(SEM) images of the studied materials possess spherical morphology with
induced porosity due to change in annealing temperature. The computed size of nanoparticles from Transmission Electron Microscopy (TEM) was 21nm. The UVVisible Spectroscopy revealed that the band gap decreased with increase of the
temperature from 3.05eV to 2.82eV. Photoluminescence (PL) spectrum of ZnO nanoparticles shows that oxygen vacancy related defects increased as the temperature increases from 500°C to 800°C and decreased beyond 800°C. The wear
resistance of ZnO nanoparticles is found to increase with increase of temperature owing to the generation of oxygen vacancies. The maximum friction coefficient was assigned to largest grain size
Structural, Ferroelectric, Dielectric and Piezoelectric Studies of Yttrium Substituted SrBi2Nb2O9 Lead-free Relaxor Ceramics
No full textFerroelectric ceramic compositions SrBi2–xYxNb2O9 (x = 0.0, 0.2, 0.4, 0.6 and 0.8) were prepared via conventional solid-state route with high density (92-99%) establishing the sintering conditions. X-ray diffraction studies confirmed
the orthorhombic structure. The micrographs obtained from scanning electron microscopy showed the presence of well packed and randomly oriented needle-shaped grains with an average grain size of 1.624 m. FTIR and Raman studies on these samples indicated the growth of single phase
perovskite material. From the dielectric studies, the phase transition temperature (Tc ) of strontium bismuth niobate (SBN) was found to be 430oC, whereas the Tc of yttrium substituted SBN (SBYN) was found to decrease from 400o to 370oC. The transition was diffuse and frequency dependent which is a characteristic behavior of relaxor material. The diffuseness
parameter () was computed for all the compositions. P-E loop measurements showed a decrease in the parameters Ps
, Pr and Ec in yttrium substituted SBN compared to SBN. Piezoelectric studies in SBN and SBYN estimated kp
, d33, g33 and Qm values. Cole-Cole plots were obtained from studies on SBN and SBYN at different temperatures in the frequency range 50 Hz to 1 MHz. The activation energy values were computed
Effect of post deposition annealing on the electrical properties of YSZ thin films deposited by pulsed laser technique
No full textIn this paper we report the detailed analysis of the effect of in-situ annealing on the electrical properties of yttrium stabilized zirconium oxide (YSZ) thin films grown by pulsed laser deposition on silicon substrates. The optimized metal/YSZ/Si devices showed low leakage current, good dielectric strength and a breakdown field strength of 4.13 MV/cm. The magnitudes of flat band voltage, and interfacial charge density have been extracted from the capacitance-voltage (C-V) characteristics of the MOS structure. The C-V characteristics show a small hysteresis which indicates the presence of traps. The observed shift in the flat band voltage and hysteresis are explained with the help of X-ray photoelectron spectroscopy. From the XPS depth profile analysis of the samples it was found that as we go from the surface to the interface, oxygen concentration in the deposited film decreases, i.e. the oxide becomes zirconium rich. This has been correlated with the observed electrical properties
Internet of Medical Things (IoMT)-An overview
No full textInternet of Things (IoT) plays a vital role in the
field of healthcare. The development of smart sensors, smart
devices, advanced lightweight communication protocols made the possibility of interconnecting medical things to monitor biomedical signals and diagnose the diseases of patients without human intervention and termed as Internet of Medical Things (IoMT). This paper portrays an overview of Internet of Medical Things based remote healthcare, tracking ingestible sensors, mobile health, smart hospitals, enhanced chronic disease treatment. Index Terms—Internet of things(IoT), Internet of medical things(IoMT), smart hospitals, ingestile sensors, mobile health, chronic disease treatmen