Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

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VIT University

More than fifty percent Indian population do not have access to electricity in daily lives. The distance between the power generating stations and the distribution centers forms one of the main reasons for lack of electrification in rural and remote areas. Here lies the importance of decentralization of power generation through renewable energy resources. In the present world, electricity is predominantly powered by alternating current, but most day to day devices like LED lamps, computers and electrical vehicles, all run on DC power. By directly supplying DC to these loads, the number of power conversion stages was reduced, and overall system efficiency increases. Replacing existing AC network with DC is a humongous task, but with power electronic techniques, this project intends to implement DC grid at a household level in remote and rural areas. Proposed work was designed and simulated successfully for various loads amounting to 250 W through appropriate power electronic convertors. Maximum utilization of the renewable sources for domestic and commercial application was achieved with the proposed DC topology. © Published under licence by IOP Publishing Ltd.

Department of Energy and Power Electronics

School of Electrical Engineering

Vellore Campus

Department of Database Systems

School of Computer Science and Engineering

Department of Automotive Engineering

School of Mechanical Engineering

Fulltext

IOP Conference Series: Materials Science and Engineering

DC grid for home applications

Seminal fluid is the secretion from many glands comprised of several organic and inorganic compounds including free amino acids, proteins, fructose, glucosidase, zinc, and other scavenging elements like Mg2+, Ca2+, K+, and Na+. Therefore, in the view of development of novel approaches and proper diagnosis to male infertility, overall understanding of the biochemical and molecular composition and its role in regulation of sperm quality is highly desirable. Perhaps this can be achieved through artificial intelligence. This study was aimed to elucidate and predict various biochemical markers present in human seminal plasma with three different neural network models. A total of 177 semen samples were collected for this research (both fertile and infertile samples) and immediately processed to prepare a semen analysis report, based on the protocol of the World Health Organization (WHO [2010]). The semen samples were then categorized into oligoasthenospermia (n=35), asthenospermia (n=35), azoospermia (n=22), normospermia (n=34), oligospermia (n=34), and control (n=17). The major biochemical parameters like total protein content, fructose, glucosidase, and zinc content were elucidated by standard protocols. All the biochemical markers were predicted by using three different artificial neural network (ANN) models with semen parameters as inputs. Of the three models, the back propagation neural network model (BPNN) yielded the best results with mean absolute error 0.025, -0.080, 0.166, and -0.057 for protein, fructose, glucosidase, and zinc, respectively. This suggests that BPNN can be used to predict biochemical parameters for the proper diagnosis of male infertility in assisted reproductive technology (ART) centres. Abbreviations: AAS: absorption spectroscopy; AI: artificial intelligence; ANN: artificial neural networks; ART: assisted reproductive technology; BPNN: back propagation neural network model; DT: decision tress; MLP: multilayer perceptron; PESA: percutaneous epididymal sperm spiration; RBFN: radical basis function network; SRNN: simple recurrent neural network; SVM: support vector machines; TSE: testicular sperm extraction; WHO: World Health Organization. © 2016 Taylor &amp; Francis.

VIT Unitversity

World University root node

Department of Biotechnology

School of Bio Sciences and Technology

Department of Mathematics

School of Advanced Sciences

Systems Biology in Reproductive Medicine

Validation of artificial neural network models for predicting biochemical markers associated with male infertility

Adaption of global culture in education system has paved an imbalance in intake and pass out ratio of educational institutions. It opens up an enormous research work to try balancing this imbalance. This paper surveys on the research works focusing on students’ performance prediction,analysis to improve performance,increase student retention published since 2004 to till date. © 2016,International Journal of Pharmacy and Technology. All rights reserved.

Department of Information Technology

School of Information Technology and Engineering

International Journal of Pharmacy and Technology

Prediction of student performance in educational data mining - A survey

Digital universe in India is doubling in size every two years and will multiply nine-fold between 2014 and 2020. As per ASSOCHAM, the value of Indian e-commerce market in 2012 was $8.5 billion and $16 billion in 2013 and it is estimated to be $56 billion in 2023. Sources of e-commerce depend on the effective shopping, prompt delivery and increased use of online payment mechanism. Online shopping has changed the face of marketing globally. It has helped in easier, simpler and faster business transactions. Today each and every household is using online shopping. India being a highly populated country is positively transforming towards online shopping. Therefore there is a huge scope for both business and teenagers in India for online selling and buying household goods. As the Indian population is adding more educated and expert in internet technology, online shopping is moving drastically. In this background, the present descriptive study is an attempt to investigate the important factors influencing teenager’s behaviour, attitude and perception towards online shopping in Vellore district of Tamil Nadu in India. © Ajay Kumar Sharma, 2016.

Department of Commerce

School of Social Sciences & Languages

Journal of Internet Banking and Commerce

Factors influencing youngsters’ behavior towards online shopping in Vellore district of Tamilnadu, India

The current work was designed to isolate and characterize chitin degrading bacteria. Among the 55 bacterial colonies isolated from 7 different soil samples, 4 isolates were capable of degrading chitinase, among which one strain VITSD3 was found to be potent. Based on the morphological, biochemical and molecular characterization of VITSD3 the isolate was confirmed as Bacillus cereus (Genbank accession number: KC961638), designated as Bacillus cereus VITSD3. The crude enzyme had a total activity of 220 U, precipitated with 44.8 U and 22.5 U for dialysed sample. The hydrolysed product NAG (N-Acetyl Glucosamine) from chitin was analysed by high-pressure liquid chromatography (HPLC).The molecular weight of the chitinase was determined using SDS PAGE and found to be 55 kDa. The partially purified chitinase produced from Bacillus cereus VITSD3 showed antifungal activity against Aspergillus fumigatus (18 mm), Aspergillus niger (6 mm) and Aspergillus flavus (15 mm). Hence the investigation suggests a potential benefit of partially purified chitinase extracted from Bacillus cereus VITSD3 which will serve as an excellent antifungal potential with therapeutic use. © 2015 Universidade Federal de Uberlandia. All rights reserved.

Department of Bio-Medical Sciences

Bioscience Journal

Production and partial purification of antifungal chitinase from Bacillus cereus VITSD3

The continuous growth of electronic commerce websites, its success and failure has stimulated great interest in analyzing consumer behavior towards e-commerce websites. Given the significant rise in the online users, better understanding of consumers allows better marketing strategies to be designed. Conventional methods are out dated in accessing the consumer behavior towards e-commerce websites. In this paper web usage mining is used to extract the consumer behavior from the web log file and K-Means Clustering algorithm is used to analyze the consumer behavior data. © Research India Publications.

International Journal of Applied Engineering Research

Analyzing consumer behavior towards E-Commerce website using web usage mining

Induction motors are the workhorses of industries. The two viable speed control schemes for the induction motor are V/f and indirect field oriented control (IFOC) technique. The voltage source inverter is the conventional power converter employed in the drive scheme. Recently, in medium power applications the multilevel inverters (MLI) are gaining more attention due to their high performance. In this work an attempt is made to develop an MLI fed induction motor drive with V/f control as well as with IFOC technique. The closed loop drive scheme is built and simulated using Matlab / Simulink. The performance of the drive scheme with both the control techniques are exhaustively studied under various conditions and the results are presented. Simulation results of IFOC scheme are provided as it exhibits better dynamic performance compared with the V/f scheme. The performance parameters of the drive with both the control schemes are compared and tabulated. © 2013 IEEE.

2013 Annual IEEE India Conference (INDICON)

Performance analysis of MLI fed induction motor drive with IFOC speed control