National Institute of Technology, Karnataka

About: National Institute of Technology, Karnataka is a education organization based out in Mangalore, Karnataka, India. It is known for research contribution in the topics: Computer science & Corrosion. The organization has 5017 authors who have published 7057 publications receiving 70367 citations.

Polyoxovanadate inhibition of Escherichia coli growth shows a reverse correlation with Ca2+-ATPase inhibition

Abstract: Recently, a global analysis of the structure–activity-relationship of a series of polyoxometalates (POMs) revealed that the most active POMs were ascribed to be polyoxovanadates (POVs), especially decavanadate (V10), which was very active against certain bacteria (Bijelic et al., Chem. Commun., 2018). The present study explores this observation and compares the effects of three POVs namely MnV11, MnV13 and V10 against Escherichia coli growth. It was observed that MnV11 presents the lowest growth inhibition (GI50) value for Escherichia coli followed by the MnV13 compound, being about 2 times lower than that of V10; respectively, the values obtained were 0.21, 0.27 and 0.58 mM. All three compounds were more effective than vanadate alone (GI50 = 1.1 mM) and also than decaniobate, Nb10 (GI50 > 10 mM), an isostructural POM of V10. However, the POVs exhibiting the highest antibacterial activity (MnV11) were shown to have the lowest Ca2+-ATPase inhibitor capacity (IC50 = 58 μM) whereas decavanadate, which was also very active against this membranar ATPase (IC50 = 15 μM), was less active against bacterial growth, suggesting that POV inhibition of ion pumps might not be associated with the inhibition of Escherichia coli growth.

An E-Learning System with Multifacial Emotion Recognition Using Supervised Machine Learning

Abstract: E-Learning systems based on Affective computingare popularly used for emotional/behavioral analysis of the users. Emotions expressed by the user is depicted by detecting the facialexpression of the user and accordingly the teaching strategies willbe changed. The present eLearning systems mainly focus on thesingle user face detection. Hence, in this paper, we proposemultiuser face detection based eLearning system using supportvector machine based supervised machine learning technique. Experimental results demonstrate that the proposed systemprovides the accuracy of 89% to 100% w.r.t different datasets(LFW, FDDB, and YFD). Further, to improve the speed ofemotional feature processing, we used GPU along with the CPUand thereby achieve a speedup factor of 2.

Local liquid holdups and hysteresis in a 2‐D packed bed using X‐ray radiography

Abstract: An X-ray visualization technique has been used for the quantitative determination of local liquid holdups distribution and liquid holdup hysteresis in a nonwetting twodimensional (2-D) packed bed. A medical diagnostic X-ray unit has been used to image the local holdups in a 2-D cold model having a random packing of expanded polystyrene beads. An aqueous barium chloride solution was used as a fluid to achieve good contrast on X-ray images. To quantify the local liquid holdup, a simple calibration technique has been developed that can be used for most of the radiological methods such as gamma ray and neutron radiography. The global value of total liquid holdup, obtained by X-ray method, has been compared with two conventional methods: drainage and tracer response. The X-ray technique, after validation, has been used to visualize and quantify the liquid hysteresis phenomena in a packed bed. The liquid flows in preferred paths or channels that carry droplets/rivulets of increasing size and number as the liquid flow rate is increased. When the flow is reduced, these paths are retained and the higher liquid holdup that persists in these regions leads to the holdup hysteresis effect. Holdup in some regions of the packed bed may be an order of magnitude higher than average at a particular flow rate.

Backstepping sliding mode control of a variable speed wind turbine for power optimization

Abstract: To optimize the energy capture from the wind, wind turbine (WT) should operate at variable speed. Based on the wind speed, the operating regions of the WT are divided into two parts: below and above the rated wind speed. The main aim at below rated wind speed is to maximize the energy capture from the wind with reduced oscillation on the drive train. At above rated wind speed, the aim is to maintain the rated power by using pitch control. This paper presents the control of WT at below rated wind speed by using backstepping sliding mode control (BSMC). In BSMC, generator torque is considered as the control input that depends on the optimal rotor speed. Usually, this optimal rotor speed is derived from effective wind speed. In this paper, effective wind speed is estimated from aerodynamic torque and rotor speed by using the modified Newton Rapshon (MNR) algorithm. Initially, a conventional sliding mode controller (SMC) is applied to the WT, but the performance of the controller was found to be less robust with respect to disturbances. Generally, WT external disturbance is not predictable. To overcome the above drawback, BSMC is proposed and both the controllers are tested with mathematical model and finally validated with the fatigue, aerodynamics, structures, and turbulence (FAST) WT simulator in the presence of disturbances. From the results, it is concluded that the proposed BSMC is more robust than conventional SMC in the presence of disturbances.