National Institute of Technology, Karnataka
Education•Mangalore, Karnataka, India•
About: National Institute of Technology, Karnataka is a(n) education organization based out in Mangalore, Karnataka, India. It is known for research contribution in the topic(s): Corrosion & Cloud computing. The organization has 5017 authors who have published 7057 publication(s) receiving 70367 citation(s).
Topics: Corrosion, Cloud computing, Microstructure, Alloy, Heat transfer
Papers published on a yearly basis
01 Jan 2019
TL;DR: In this paper, the authors have discussed the usage of different types of membranes for FO desalination application and their performances enhancement by suitable modification has been discussed, as well as a significant amount of work has been carried out to produce high-performance FO membrane for Desalination.
Abstract: Rapid population growth increases the demand for freshwater. Membrane technology is playing a dynamic role in the production of clean water from seawater and wastewater. The desalination of seawater using forward osmosis (FO) is an emerging technology to produce freshwater, as it is energy efficient than the conventional processes. In recent days, a significant amount of work has been carried out to produce high-performance FO membrane for desalination. In this chapter, usage of different types of membranes for FO desalination application and their performances enhancement by suitable modification has been discussed.
01 Sep 2010
TL;DR: An algorithm for this optimization problem, as well as a greedy scheme with some performance guarantees for a variant of the problem that seeks to minimize a simpler objective are proposed.
Abstract: A scheme for consensus formation is considered wherein the value of a certain variable associated with the nodes of a network is fixed a priori for a prescribed set of K nodes, and allowed to propagate throughout the network through an averaging process that mimics a gossip algorithm. The objective is to find the best choice of these K nodes that will achieve the fastest convergence to consensus. This objective is captured by the Perron-Frobenius eigenvalue of the resultant sub-stochastic matrix, which then is the quantity one seeks to minimize. We propose an algorithm for this optimization problem, as well as a greedy scheme with some performance guarantees for a variant of the problem that seeks to minimize a simpler objective. Some other related formulations are also considered.
15 Mar 2013-Desalination
TL;DR: Graphene oxide (GO) dispersed polysulfone (PSf) mixed matrix membranes were prepared by wet phase inversion method in this paper, where the morphology of membranes was studied using scanning electron microscope (SEM) images.
Abstract: Graphene oxide (GO) dispersed polysulfone (PSf) mixed matrix membranes were prepared by wet phase inversion method. The morphology of membranes was studied using scanning electron microscope (SEM) images. The variation in hydrophilicity was studied by measuring surface wettability and water swelling experiments. The performance of membranes in terms of pure water flux and salt rejection was studied. SEM images depict enhanced macrovoids, while the contact angle data reveals that, GO incorporated membrane surface is moderately hydrophilic. Membranes exhibited improved salt rejection after GO doping. Membrane with 2000 ppm GO loading has exhibited maximum of 72% Na2SO4 rejection at 4 bar applied pressure. The salt rejection seems to depend on pH of the feed solution and it has been witnessed that the salt rejection showed an increasing trend with increase in the pH.
01 Jan 2015-Aquatic Procedia
TL;DR: In this paper, the authors discuss briefly about variable infiltration capacity model (VIC), TOPMODEL, HBV, MIKESHE and soil and water assessment tool (SWAT) model.
Abstract: Various ongoing researches are there on topics like which model will give more compatible results with that of observed discharges. It was argued that even complex modeling does not provide better results. Climate change and soil heterogeneity has got an important role in finding out surface runoff. In this paper, we are going to discuss briefly about variable infiltration capacity model (VIC), TOPMODEL, HBV, MIKESHE and soil and water assessment tool (SWAT) model. VIC performs well in moist areas and can be efficiently used in the water management for agricultural purposes. Requirement of large data and physical parameters makes the use of MIKE SHE model limited to smaller catchments. Only a little direct calibration is required for SWAT model to obtain good hydrologic predictions. HBV model gives satisfactory results and TOPMODEL can be used in catchments with shallow soil and moderate topography.
01 Jun 2014-Applied Soft Computing
TL;DR: This paper reviews the state-of-the-art and focuses over a wide range of applications of SVMs in the field of hydrology, providing a brief synopsis of the techniques of SVM and other emerging ones (hybrid models), which have proven useful in the analysis of the various hydrological parameters.
Abstract: In the recent few decades there has been very significant developments in the theoretical understanding of Support vector machines (SVMs) as well as algorithmic strategies for implementing them, and applications of the approach to practical problems. SVMs introduced by Vapnik and others in the early 1990s are machine learning systems that utilize a hypothesis space of linear functions in a high dimensional feature space, trained with optimization algorithms that implements a learning bias derived from statistical learning theory. This paper reviews the state-of-the-art and focuses over a wide range of applications of SVMs in the field of hydrology. To use SVM aided hydrological models, which have increasingly extended during the last years; comprehensive knowledge about their theory and modelling approaches seems to be necessary. Furthermore, this review provides a brief synopsis of the techniques of SVMs and other emerging ones (hybrid models), which have proven useful in the analysis of the various hydrological parameters. Moreover, various examples of successful applications of SVMs for modelling different hydrological processes are also provided.
Showing all 5017 results
|Alexander P. Lyubartsev||49||184||9200|
|Arun M. Isloor||38||261||6272|
|M. C. Ray||30||115||2662|
|Airody Vasudeva Adhikari||30||119||2832|
|Ian R. Lane||27||129||2947|
|D. Krishna Bhat||26||95||1715|
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