Visvesvaraya Technological University
  • Belgaum, Karnataka, India
Recent publications
Simple redox reactions at ambient conditions have prepared manganese dioxide (MnO2) and MnO2/conducting polymer nanocomposites. Keeping the aqueous KMnO4 solution as a manganese source, MnO2, MnO2/polyaniline, and MnO2/polypyrrole nanocomposites are synthesized using ethylene glycol, aniline, and pyrrole as reducing agents, respectively. The powder X-ray diffraction analysis reveals that the prepared MnO2 and MnO2-based nanocomposites are amorphous. Fourier transform infrared spectral measurements further confirm the presence of functional groups. The change in the morphology of all samples was observed through scanning electron microscopy. The AC electrical conductivity and dielectric measurements are taken in the applied frequency range of 10 Hz–100 MHz. With the help of these experimental parameters, the electrical properties of MnO2, MnO2/polyaniline, and MnO2/polypyrrole nanocomposites are analyzed. Out of all prepared nanocomposites, the results signpost better conductivity for Ppy-MnO2 nanocomposite, and its conductivity enhances with the rise in applied frequency. Based on the observations, manganese-based conducting polymer composites can be used to develop electronic device-level applications. Also, the preparation method adopted in this study is simple, and these materials can produce on a large scale.
With the advancement of technology in image capturing, people are accustomed to high-resolution images. One of the primary necessities of an image capturing system is to provide the same. However, in many cases, the image resolution may not be reaching the expectations of the user which leads to a decrease in user experience. This is a common phenomenon that occurs when the images are captured in low light or if the image encounters a distortion either because of lack of exposure or the image capturing devices may be equipped with a small size sensor. In this work, a resolution enhancement technique using the concepts of curvelet transform and iterative back projection is presented. Sparse representation of images can be enhanced using a combination of curvelet transforms with iterative back projection. Application of curvelet transform along with iterative back projection algorithm on low light images results in enhancing the resolution of the images. The resultant images from here then passed through the inverse transform block and gives an image with contrast enhancement which leads to the user experience improvement. The antiquated image enhancement with improvement in the resolution is validated with the measurement of peak signal-to-noise ratio and structural similarity index. The usage of curvelet transform with iterative back projection leads to the restoration of the image resolution by minimizing the distortions, thus leading to an enhanced image whose edge details are retained.
Simple, accurate and robust analytical methods have been developed and validated for the determination of favipiravir (FVPR) by RP-HPLC and UV spectroscopy techniques as per the ICH guidelines. In the RP-HPLC method for FVPR determination, the mobile phase was ammonium acetate buffer pH 6.5 in pump Aand methanol in pump B. The C18 (Sunfire) 5 μm, 4.6 × 250 mm column was used as a stationary phase, and the detection wavelength was at 323 nm. Under these conditions, FVPR was eluted as a sharp peak at 2.65 min and the overall time taken for each injection was 10 min. In case of the UV spectroscopy method, standard FVPR solutions were prepared with pure ethanol and scanned from 250 to 400 nm and a flourishing spectrum was obtained at 323 nm. Hence, the wavelength of 323 nm was fixed for the whole process of validation in both techniques. The limit of detection (LOD) and limit of quantification (LOQ) in the RP-HPLC method were 1.0 and 3.5 μg/mL, respectively, and the linearity was established in the 10 to 50 μg/mL range. In the UV spectroscopy method, the LOD and LOQ values were found to be 3.5 and 12 μg/mL, respectively, and the linearity was established within 20 to 60 μg/mL range. The regression coefficient was found to exceed 0.999 in both methods. The proposed RP-HPLC and UV spectroscopy techniques are simple, accurate, rugged and robust.
Wind energy is one of the most abundantly available renewable energy, which is clean and promising source for electric energy conversion. Vertical Axis Wind Turbine (VAWT) possesses technological, environmental, and economic benefits over Horizontal Axis Wind Turbine. Thus, the present work investigates on the design and analysis of two airfoil profiles (NACA 0012 & NACA 0018) with VAWT using ANSYS Fluent 2020 R2 solver. The structural stability (deformation) of Aluminum blades at varied wind speeds throughout the energy conversion is the prime focus of the present work. Developed airfoil models showed the structural stability even at extreme pressure, with minimal deformation, stress and strain. The velocity and pressure contours at diverse wind speeds (3, 5 and 10 m/s) are analyzed. It is evident that, the turbine blade were with uniform rotation even under turbulent flow. The outcomes of the analysis on the developed models showed good agreement to predict the torque and power. Therefore, it can be practically implemented to form and join using Friction Stir Processing.
Green chemistry, which is an application of a set of principles to decrease or eliminate the use or creation of hazardous chemicals in the design, manufacture, and use of chemical commodities, is one of the most appealing concepts in chemistry for sustainability. Green chemistry has grown in popularity as a consequence of the understanding that environmentally friendly products and methods save mother nature over time. A fundamental key of synthetic chemistry is the creation of ecologically acceptable methods for the synthesis of organic molecules. In many biological applications, new molecules have been synthesized using environmentally friendly processes throughout the past few decades. It is also observed that, in the cycloaddition processes, nature-friendly approaches were focused significantly to avoid environmental pollution caused by toxic solvents and other additives. Hence, we as responsible chemists highly motivated to showcase the green synthetic methods adopted for cycloaddition reactions. In this study, we have reviewed nature-friendly methods utilized for the synthesis of new compounds via Diels–Alder and 1,3-dipolar cycloaddition reactions.
3D printing technology is also known as additive manufacturing technology where the products are manufactured layer by layer. In recent years, huge research is taking place in this field to increase the strength of products by varying the printing process parameters with respect to different materials for various applications. In this research, efforts have been made to decrease the surface roughness for PETG-printed specimen using fused deposition modeling (FDM) process through Taguchi method. The process parameter chosen for the current research is raster angle (RA), infill density (ID), and layer thickness (LT) by keeping other process parameter constant. For the surface texture (roughness) of FDM-printed specimens, three level of values is considered for each process parameter, and correlations between these process parameters were examined which is not found in the literature for PETG specimens. Using design of experiment (DOE) via L27 orthogonal array study has been started. The obtained experimental data were analyzed to examine the impact of each process parameter on the top surface roughness. To assess if process variables have any significant features, the analysis of variance (ANOVA) is performed. The layer thickness has greater than 73% influence on surface roughness, followed by infill density and raster angle, according to the ANOVA results. The results from investigation of Taguchi methods showed that from the selected process parameter 0.1-mm layer thickness, 90% infill density and 60° raster angle are found to be the optimum for better surface finish at 245 °C and at 45 mm/s print speed. The research is focused on a simple yet effective method for estimating surface roughness over various surfaces of FDM specimens using PETG material. .
Identification of wheat seed varieties is crucial for meeting market demands. The automated image-based approaches proposed in this paper are used to identify wheat seeds from three different types, namely Canadian, Rosa, and Kama. The effective classification methods, namely Artificial Neural Network with Back Propagation (BPNN), Support Vector Machine (SVM), and k-Nearest Neighbor (k-NN) are adopted for wheat variety identification. The classifiers are trained using morphological features derived from the singleton wheat kernel images. The k-NN, BPNN, and SVM classifiers have yielded the classification efficiencies of 94.23%, 90.35% and 83.57%, respectively.
Content-based image retrieval, also known as query by image content is the application of computer vision techniques to the image retrieval problem, that is, the problem of searching for digital images in large databases. The usage of digital images has been increased enormously from the last decade due to the drastic growth in storage and network technology. These technological changes have led the professional users to use, store and manipulate the remotely stored images. Information Retrieval (IR) deals with location and retrieval of related documents or images on the basis of user inputs such as keywords or example as a query from the repository. Hence, to throw a light into this chosen research topic, we are carrying out an integrated analysis of HSV color histogram characteristics with contour based concepts could be used to improve the retrieval system performance in CBIR.
Lignocellulosic agricultural biomasses and wood are the two most important natural sources of cellulose available on the planet. When chemically treated, cellulose is the world’s most common and widely used biopolymer, with properties such as low price, good toughness, good biocompatibility and good thermal stability. In this study, nanocellulose was extracted from ragi stalk, mango wood and groundnut husk. The cellulose was alkali-treated with NaOH and bleached with sodium chlorite to remove lignin and hemicellulose. Ionic liquid (1-butyl-3-methylimidazolium chloride ([Bmim]Cl) solvent was used to treat the obtained cellulose. FTIR spectra highlight the functional groups and substantial conversion of cellulose to nanocellulose. The crystalline or semi-crystalline nature of synthesized nanocellulose was illustrated by XRD. The TEM images record the size of synthesized nanocellulose between 11.12 and 31.16 nm. The reduction in size is mainly due to ultrasonication and centrifugation. The thermal stability of the obtained nanocellulose was evidenced using TGA/DTA. The thermal studies insight that the synthesized nanocellulose samples possess superior degradation temperature up to 473.8 ºC.
It is ended that from past few decades the consumption of fossil fuel as measuring at faster rates in order to satisfy the needs of mankind. Many researches are working in the process of measuring the efficiency of the engine. Thermal coating is a process applying a layer of coated materials on the surface of any metallic part. In this project working of the zirconium di oxide (ZrO 2 ) is used on coated material and NiCrAl is used on subtract material. A 0.1mm layer of zirconium di oxide is coated on top surface of the piston then the performance of the IC engine is evaluated. The performance parameter of the coated piston is compared with performance parameter of uncoated piston. The material efficiency and Brake power of the coated piston is expected to increase, since the melting point temperature of zirconium di oxide is more than 2500 degree Celsius.
Although noise management has received a lot ofattention recently, image deblurring is still difficult. Imageswithout any noisy pixels are the focus of the current deblurringnetworks. To explicitly or implicitly lessen the impact of noisypixels on image deblurring, existing methods primarily relyon repetitive noise detection stages. However, these iterativeoptimization procedures and heuristic operations, which aredifficult and time-consuming, are frequently used in these noisypixels detection steps. In this paper we propose a cascaded modelof two separate networks which will handle the noisy pixelswithout any reduction in image quality. Our model aims todenoise an image first and then deblur it. In addition, it wasfound that deblurring an image first, then denoising it, producedbetter results than training a deblurring network on noisy images.Numerous tests demonstrate that this cascaded network performscompetitively in terms of PSNR and SSIM.
2022): Inhibitory effect of gallic acid from Thunbergiamysorensis against α-glucosidase, α-amylase, aldose reductase and their interaction: Inhibition kinetics and molecular simulations, Journal of Biomolecular Structure and Dynamics, ABSTRACT In this exploration, we assessed the antihyperglycaemic properties of methanol extract of flowers of Thunbergia mysorensis (MeT) against a-glucosidase, a-amylase and aldose reductase enzymes for the effective management of postprandial hyperglycemia. Hyperglycemia occurs when the body lacks enough insulin or is unable to correctly utilize it. MeT inhibited both the carbohydrate digestive enzymes (a-glucosidase and a-amylase) and aldose reductase, which are vital for the therapeutic control of postprandial hyperglycaemia. MeT was also found to have significant antioxidant activity. Using several spectroscopic approaches, the primary active component found in MeT was identified as gallic acid. With low Ki values, gallic acid significantly inhibited a-glucosidase (30.86 mg/mL) and a-amylase (6.50 mg/mL). Also, MeT and gallic acid both inhibited aldose reductase effectively, corresponding to an IC 50 value of 3.31 and 3.05 mg/mL. Our findings imply that the presence of polyphenol compounds (identified via HPLC analysis) is more likely to be responsible for the antihyperglycaemic role exhibited by MeT via the inhibition of a-glucosidase and the polyol pathway. Further, gallic acid interacted with the key residues of the active sites of a-glucosidase (À6.4 kcal/mol), a-amylase (À5.8 kcal/mol) and aldose reductase (À5.8 kcal/mol) as observed in the protein-ligand docking. It was also predicted that gallic acid was stable inside the binding pockets of the target enzymes during molecular dynamics simulation. Overall, gallic acid derived from MeT via bioassay-guided isolation emerges as a natural antidiabetic drug and can be taken into in vivo and clinical studies shortly. ARTICLE HISTORY
The corrosion process can be seen as a widespread phenomenon, which is both pervasive and unstoppable. This is an undesirable phenomenon that reduces the life of materials and takes away their beauty. Potentiodynamic and electrochemical impedance tests are used to explore the corrosion inhibition abilities of a room temperature columnar liquid crystalline perylene bisimide (PBIO10) on mild steel (MS) samples in 1 M HCl. The inhibitor PBIO10 was demonstrated to be an outstanding corrosion inhibitor, with a maximum inhibition efficiency of 76%. In light of potentiometric polarization results, corrosion inhibition was achieved as the inhibitor getting adsorbed on the metal, and they fit into the category of anodic inhibitors. The protective layer was examined from SEM to confirm the protective coating generated on the MS surface. The increase in contact angle confirms the formation of a uniform layer on the MS surface. Analysis of the optical textures observed in POM, the nature of the mesophase under examination to columnar rectangular (Colr) phase. From the TGA, it was found that PBIO10 exhibits higher thermal stability u to 370 ℃. The density functional theory (DFT) and Monte Carlo simulation approach were used to investigate the relationship between molecular structure and inhibitory efficacy. The thermal behavior of PBIO10 was investigated by polarizing optical microscopy (POM), differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), and X-ray diffraction (XRD) studies. The phase transition from crystal to LC phase was at first examined with the help of POM observation. Graphical Abstract
In underwater wireless sensor networks, the optimization strategies for localization might be seen as a new boon for the localization of sensor nodes (UWSNs). The techniques for optimization are those that repair the incorrect value, adapt it to the situation, and correct it. Because the algorithm could adapt to the constantly changing environment, it was widely used in terrestrial applications, and the same can be extended to the underwater environment with modifications. To address the localization issue that arises in UWSNs, the Underwater Salp Swarm Algorithm (USSA), a nature-inspired node localization algorithm, has been presented. With the help of this technique, an effort to discover a solution to the localization problem as an optimization problem is considered. The proposed algorithm is accessed in a simulated water environment. The energy is assigned to the anchor well as non-localized nodes, after deploying them in the simulated underwater network. The suggested algorithm is compared with other optimization algorithms, such as UPSO and UBOA, with reference to the computing time, localization accuracy, and the number of localized nodes. It is possible to localize a greater number of nodes in a much faster and more efficient way by considering the proposed algorithm.
In the present work, experiments have been carried out to analyze the feasibility of utilizing individual sunflower oil (SFO), palm oil (PO), mineral oil (MO), blends of mineral-sunflower oil (MO:SFO), and mineral-palm oil (MO:PO) to lubricate the specimen mounted in four-ball tribometer. The tribological parameters such as friction coefficient, wear scar diameter (WSD), wear mechanism, and vibration characteristics were obtained from the ball specimen lubricated by using above mentioned oil samples as per ASTM D4172 standards. The experimental observations indicated that the MO:PO oil blend sample led to a decrease in friction coefficient about 35%, 20%, 6%, and 41% than that of individual MO, PO, SFO, and MO: SFO blends respectively. Further, MO:PO blend resulted a reduction in WSD about 94%, 95%, and 5% in comparison to PO, SFO, and MO: SFO samples respectively. The MO:PO oil blends showed a reduction in mass loss and vibration amplitudes by 6% and 5% respectively than that of PO oil lubrication. This is mainly credited to the synergic effect of fatty acid molecules and additives present in vegetable and mineral oils. The results obtained in the experimental investigation provided an insight to the suitability of MO:PO biobased lubricant in enhancement of tribological properties thereby minimizing the friction coefficient, WSD, and vibration response than that of individual PO, SFO and MO:SFO oil blend.
Nanoscale ferrite magnetic materials have been applicable as electronic materials due to their tuned structural, magnetic and optical behaviors. In the present research, non-stoichiometric potassium-substituted magnesium ferrite nanomaterials, Mg0.5+xK1−2xFe2O4 (0 ≤ x ≤ 0.35), have been prepared by a cost-effective citrate precursor method annealed at a low temperature of 450°C. The average crystallite size was calculated using a W–H plot and ranged from 22 to 33 nm. HRTEM analysis determined the morphology, d-spacing, and particle size (ranging from 26 to 37 nm). EDAX analysis revealed the absence of impurity phases in the prepared nanomaterials. FTIR study showed that ferrite nanomaterial belonged to the Fd-3 m space group, and the bond length decreased with K+ ion concentration. The band gap was evaluated by the Tauc plot, which reduced from 2.39 eV to 2.12 eV with decreasing K+ content. Zeta measurements revealed the stability of the prepared material in the colloidal phase. The saturation magnetization increased from 4.53 to 22.15 emu/g with the decreasing molar concentration of K. The ferroelectric measurement demonstrated the decreasing leakage currents, which indicates the possible use of ferrites in various electronic fields. The hydroelectric cell performance of the prepared materials showed a decrease in voltage–current slope with increased potassium substitution, which is indicative of the increase in material resistance. The room temperature photoluminescence analysis represented all emission peaks in the visible range. Thus, the non-molar and low-temperature synthesis of K-substituted ferrites may be advantageous for various areas of science and technology due to their tuned optical, structural, magnetic, ferroelectric, and voltage–current properties.
The trimanganese tetraoxide (Mn3O4) nanoparticles (NPs) belong to transition metal oxides and play a vital role in decaying the organic pollutants by harvesting light. The Mn3O4 is synthesized by solution combustion method for different metal-to-fuel ratios. The variation of crystallite sizes of Mn3O4 NPs with changes in the fuel ratio was studied by powder X-ray diffraction. The d-spacing of the HR-TEM image’s lattice fringes perfectly match the (200) plane of the XRD pattern. The surface chemistry and composition of samples was confirmed by XPS data. Absorption spectroscopy was used to estimate the optical bandgap of the prepared samples. The BET analysis revealed the decrease in surface area with the increase in crystallite size. The photocatalytic degradation of Rhodamine B (RB) with crystallites of various shapes and sizes of Mn3O4 NPs was investigated. The degradation of RB increased with the enhancement in crystallinity of the sample. The proportion of RB dye degradation was found to be 99.75% in 2 h. The oxidizer-to-fuel ratio–dependent electrochemical investigations of Mn3O4 NPs were carried out using a three-electrode setup. Mn3O4 NPs were observed to be a better supercapacitor material with a specific capacitance of 58.91 F/g at 1 A/g. Hence, the prepared Mn3O4 samples can be used in cost-effective energy storage device applications.
Synthetic small molecules have been very effective in decimating cancer cells by targeting various aberrantly overexpressed oncogenic proteins. These small molecules target proteins involved in cell cycle regulation, cell division, migration, invasion, angiogenesis, and other regulatory proteins to induce apoptosis in cancer cells. In this study, we have synthesized a novel 1,2,5-trisubstituted benzimidazole chemical library of small molecules and unveiled their anticancer potential against a panel of cancer cell lines such as Jurkat, K-562, MOLT-4, HeLa, HCT116, and MIA PaCa-2 cancer cells. The MTT assay and Trypan blue dye exclusion assay clearly unveiled the cytotoxic effect of methyl 1-benzyl-2-(4-fluoro-3-nitrophenyl)-1H-benzo[d]imidazole-5-carboxylate (TJ08) and its potential to induce apoptosis with effective IC50 of 1.88 ± 0.51, 1.89 ± 0.55, 2.05 ± 0.72, 2.11 ± 0.62, 3.04 ± 0.8, and 3.82 ± 0.25 μM against Jurkat, K562, MOLT-4, HeLa, HCT116, and MIA PaCa-2 cancer cell lines, respectively. Altered mitochondrial membrane potential was observed in HeLa, HCT116, and Jurkat cells due to TJ08 treatment, which was unveiled by JC10 staining. Induction of early and late apoptosis by TJ08 treatment was also unveiled by apoptotic analysis and immunofluorescence imaging. Cell cycle analysis distribution confirms the accumulation of cells in the S-phase in a dose-dependent manner.
The demand for electrical energy is increasing day by day due to urbanization, industrialization, and increase in the domestic load, and to cater this increase in load demand, the electrical generation has to be increased. Nowadays, most of this increase in demand is met by the generation happening through renewable energy sources. All these plants have to be interconnected with a power grid and supply the generated power to the load center. Thus, the complexity of the electrical power system has increased, and performing the computation tasks manually is a time‐consuming and tedious process, which may also lead to errors in the calculation. As the technology has advanced and the availability of high‐end computers, all these tasks can be performed by programming in digital computers. For any proposed power system network or existing network, engineering studies related to planning, designing, and operation of the system have to be performed to evaluate its reliability, safety, performance, and economics. These studies provide information to eliminate the deficiencies in the system before going into the implementation process, thus saving time and cost. Studies on the existing system have to be performed to identify the equipment overloading, failure, and maloperation based on that corrective or preventive measures can be taken. In this chapter, simulation studies related to modeling of power systems, steady‐state analysis, dynamic analysis, and voltage stability are presented. Models are developed in ETAP software and MIPOWER software for different case studies. Short circuit analysis, load flow studies, harmonic analysis, and voltage stability were studied and the results were presented.
The most recurrent side effect of diabetes is diabetic foot ulcers and if unattended cause imputations. Diabetic feet affect 15 to 25% of diabetic people globally. Diabetes complications are due to less or no awareness of the consequences of diabetes among diabetic patients. Technology leveraging is an attempt to create distinct, affordable, and simple diabetic foot diagnostic strategies for patients and doctors. This work proposes early detection and prognosis of diabetic foot ulcers using the EfficientNet, a deep neural network model. EfficientNet is applied to an image set of 844-foot images, composed of healthy and diabetic ulcer feet. Better performance is obtained compared to earlier models using EfficientNet by carefully balancing network width, depth, and image resolution. The EfficientNet performed better compared to popular models like AlexNet, GoogleNet, VGG16, and VGG19. It gave maximum accuracy, f1-score, recall, and precision of 98.97%, 98%, 98%, and 99%, respectively.
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  • The Library
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  • Department of Computer Science & Engineering (UG)
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  • Department of Computer Science & Engineering
Ashwin C Gowda
  • Computer Aided Engineering
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