Nmam Institute Of Technology
Nmam Institute Of Technology
Neelima B.,NMAM Institute of Technology
Journal of Parallel and Distributed Computing | Year: 2017
Quality of education can be enriched with better outcome in undergraduate (UG) computer science and engineering program with the introduction of High Performance Computing (HPC) courses into the UG curriculum. The paper gives the background of the author's institution, processes of curricula enhancement, infrastructure development to enable students to carry out the work and records the students' achievements academic year wise. The paper also discusses the evolution and continuous upgrading of the HPC courses along with the issues and challenges experienced. The paper gives the details about the courses along with the process of teaching and evaluation. It lists the students' research achievements with a focus on HPC, for each academic year. Although the paper has focused on UG HPC education for the past seven academic years, the author also provides additional information about HPC subjects introduced to postgraduate (PG) students of computer science and engineering at various levels in the academic year 2015-16. The paper aims to serve as reference for those faculty and students who wish to introduce similar HPC courses at their schools by making use of the best practices that helped us in providing better inputs to our students to attain laudable results. © 2017 Elsevier Inc.
Srinath M.,Malnad College of Engineering |
Hebbale A.M.,NMAM Institute of Technology
Materials Today: Proceedings | Year: 2017
The stainless steel AISI-420 widely used in the manufacture of brake discs, turbine blades, piston submerged in water pumps, injection molds.etc. The present work deals with slurry erosive wear studies of cobalt based clads developed through microwave energy in a domestic microwave oven equipped with 900 W power at 2.45 GHz.The developed clads were subjected to microstructure and sand slurry erosive wear studies were carried out. Taguchi orthogonal array L9 was used to gauge the factors affecting the wear significantly. The influence of various factors such as speed, particle size and impingement angle on wear behavior was evaluated by means S/N ratio. This study reveals the slurry speed had significantly influenced the mass loss of the developed surfaces. The most popular and highly reliable analytical technique Fuzzy logic model has been successfully used to predict the slurry erosive wear behavior. The predicted values have been compared with the experimental data. The obtained average percentage error between experimental and fuzzy logic values are 13.80%. © 2017 Elsevier Ltd.
Pai S.,NMAM Institute of Technology |
Rao R.B.K.N.,COMADEM International
Machining Science and Technology | Year: 2012
The monitoring of tool wear is a most difficult task in the case of various metal-cutting processes. Artificial Neural Networks (ANN) has been used to estimate or classify certain wear parameters, using continuous acquisition of signals from multi-sensor systems. Most of the research has been concentrated on the use of supervised neural network types like multi-layer perceptron (MLP), using back-propagation algorithm and Radial Basis Function (RBF) network. In this article, a new constructive learning algorithm proposed by Fritzke, namely Growing Cell Structures (GCS) has been used for tool wear estimation in face milling operations, thereby monitoring the condition of the tool. GCS generates compact network architecture in less training time and performs well on new untrained data. The performance of this network has been compared with that of another constructive learning algorithm-based neural network, namely the Resource Allocation Network (RAN). For the sake of establishing the effectiveness of GCS, results obtained have been compared with those obtained using Multi Layer Perceptron (MLP), which is a standard and widely used neural network. © 2012 Copyright Taylor and Francis Group, LLC.
Santhosh T.C.M.,National Institute of Technology Karnataka |
Bangera K.V.,National Institute of Technology Karnataka |
Shivakumar G.K.,NMAM Institute of Technology
Solar Energy | Year: 2017
Thin films of CdSe(1-x)Te(x) (x = 0 – 1) were grown on to the glass substrates by thermal evaporation method (PVD). The effect of annealing duration on the formation of single phase ternary alloys were systematically investigated. The prepared thin films were characterized by using FE-SEM, EDS and X-ray diffractometer. The X-ray diffraction studies shows that vacuum annealed films are polycrystalline in nature, and well oriented along a preferred direction of (0 0 2) for hexagonal and along (1 1 1) for cubic crystal structure. It is observed that increase in the CdTe concentration leads to change in the crystal structure from hexagonal to cubic. The absorption coefficients and optical band gaps were evaluated from spectrometric measurements. It is observed that optical band gap can be tuned from 1.67 eV to 1.51 eV as value of x varied from 0 to 1. © 2017 Elsevier Ltd
Shenai K.,NMAM Institute of Technology
2016 1st International Conference on Sustainable Green Buildings and Communities, SGBC 2016 | Year: 2017
Energy efficiency and cost are the two key driving factors for increased usage of hybrid- and DC-microgrids in both urban and rural settings. In order to accomplish this critical objective, number of energy conversion stages from source to load need to be reduced and efficiency of every power conversion electronic block needs to be increased by carefully taking into account system-level interactions. Power converters based on wide bandgap (WBG) semiconductor switching devices such as those made on silicon carbide (SiC) and gallium nitride (GaN) semiconductors promise dramatic advances in this regard compared to the industry workhorse - the conventional silicon semiconductor. However, performance, cost and reliability need to be carefully evaluated from a systems perspective. This paper provides a review of the current state-of-the-art and emerging trends in WBG power converters for application in hybrid- and DC-microgrids. © 2016 IEEE.
Bekal S.,NMAM Institute of Technology |
Bhat N.R.,Srinivasa Institute of Technology
Energy Sources, Part A: Recovery, Utilization and Environmental Effects | Year: 2012
The substitution of mineral oil with vegetable oil as a lubricant in a CI engine is explored in this study. The experiments have been conducted with neat pongamia oil, blend of pongamia oil and mineral oil (50% V/V), and neat mineral oil as lubricants; and neat pongamia oil, blends of pongamia oil, and diesel in proportions of 20, 40, and 100, neat pongamia ester, and blends of pongamia ester and diesel in proportions of 20, 40, and 100 as fuel. For various combinations of fuel and lubricant, NOx, smoke, CO, HC, BSEC, EGT, and friction power were compared. It was found that there was no difficulty in operating the engine using the lubricants considered in this work. Further, it was found that the best results were recorded for the fuel-lubricant combination of neat pongamia as both fuel and lubricant. © 2012 Copyright Taylor and Francis Group, LLC.
Mallikappa D.N.,NMAM Institute of Technology |
Reddy R.P.,Reva institute of Technology and Management |
Renewable Energy | Year: 2012
India imports more than seventy percent of the oil it uses and is looking for alternative fuel to reduce its dependence on imports. In India, bio fuels derived from non-edible oils is considered as a renewable alternative to the fossil diesel. The cost of the biodiesel is higher than diesel and hence in this work, cardanol was used as an alternative renewable fuel for the diesel engine. The engine tests were conducted on a double cylinder, direct injection, compression ignition engine. From the engine tests, it is observed that the brake power increases (by 70% approximately) as load increases. Brake specific energy conversion decreases (by 25-30% approximately) with increase in brake power. Brake thermal efficiency increases with higher brake power and emission levels (HC, C O, NO X) were nominal up to 20% blends. © 2011 Elsevier Ltd.
Hebbale A.M.,NMAM Institute of Technology |
S S.M.,Malnad College of Engineering
Materials Today: Proceedings | Year: 2015
In the present work microwave cladding technique was progressed for enhancement of surface properties of high speed steel (SS-304). The experiments were conducted in domestic microwave oven with the help of Al2O3 shield. The clad of thickness, approximately 1mm was developed by microwave exposure at frequency 2.45GHz. The entire setup was exposed to microwave environment for about 1080s. The developed clads were characterized using FE-SEM, EDS, XRD and measurement of Vicker's microhardness. Microstructural study reveals that there is a metallurgical bond with SS-304 substrate & partial diffusion of constituent elements. Chromium was observed segregated around the cell boundaries while iron and nickel were identified inside the cells. © 2015 Elsevier Ltd.
Kallapur P.V.,Nmam Institute Of Technology |
Chiplunkar N.N.,Nmam Institute Of Technology
ACE 2010 - 2010 International Conference on Advances in Computer Engineering | Year: 2010
Recent research has provided means by which wireless sensor network with dynamic deadlines can take advantage of mobile agents for the purpose of data gathering. Already some work has been done in this direction in case of networks which are 'static' i.e., whose topology remains same once mobile agent starts its tour. This paper proposes a technique which makes mobile agent 'intelligent' enough to learn 'dynamic' changes in network topology as and when they occur, like new node getting added to network or existing node going down while taking care of dynamic deadlines of nodes. Also, we give analysis of results of applying the proposed technique on a simple real time wireless sensor network model with dynamic deadlines. Finally, paper wi l be concluded with mentioning of future directions of research. © 2010 IEEE.
Rajesh Kumar B.,Nmam Institute Of Technology |
Vardhan H.,National Institute of Technology Karnataka |
Govindaraj M.,National Institute of Technology Karnataka |
Vijay G.S.,Manipal University India
International Journal of Rock Mechanics and Mining Sciences | Year: 2013
This study aims to predict rock properties using soft computing techniques such as multiple regression, artificial neural network (MLP and RBF) models, taking drill bit speed, penetration rate, drill bit diameter and equivalent sound level produced during drilling as the input parameters. A database of 448 cases were tested for determination of uniaxial compressive strength (UCS), Schmidt rebound number (SRN), dry density (ρ), P-wave velocity (Vp), tensile strength (TS), modulus of elasticity (E) and percentage porosity (n) and the prediction capabilities of the models were then analyzed. Results from the analysis demonstrate that neural network approach is efficient when compared to statistical analysis in predicting rock properties from the sound level produced during drilling. © 2012 Elsevier Ltd.