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Institution

Motilal Nehru National Institute of Technology Allahabad

EducationAllahabad, Uttar Pradesh, India
About: Motilal Nehru National Institute of Technology Allahabad is a education organization based out in Allahabad, Uttar Pradesh, India. It is known for research contribution in the topics: Control theory & Electric power system. The organization has 2475 authors who have published 5067 publications receiving 61891 citations. The organization is also known as: NIT Allahabad & Motilal Nehru Regional Engineering College.


Papers
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Journal ArticleDOI
TL;DR: The proposed research aims to introduce a data mining approach, to discover the hidden relationships among the supplier’s pre-qualification data with the overall supplier rating that have been derived after observation of previously executed work for a period of time.
Abstract: A company must purchase a lot of diverse components and raw material from different upstream suppliers to manufacture or assemble its products. Under this situation the supplier selection has become a critical issue for the purchasing department.The selection of suppliers depends on number of criteria and the challenge is to optimize selection process based on critical criteria and select the best supplier(s). During supplier selection process initial screening of potential suppliers from a large set is vital and the determination of prospective supplier is largely dependent on the criteria chosen of such pre-qualification. In the literature, many judgments based methods are proposed and derived criteria selection from the opinion of either the customers or the experts. All these techniques use the knowledge and experience of the decision makers. These methods inherit certain degree of uncertainty due to complex supply chain structure. The extraction of hidden knowledge is one of the most important tools to address such uncertainty and data mining is one such concept to account for such uncertainty and it has been found applicable in many scenarios. The proposed research aims to introduce a data mining approach, to discover the hidden relationships among the supplier's pre-qualification data with the overall supplier rating that have been derived after observation of previously executed work for a period of time. It provides an overview that how supplier's initial strength influence its final work performance.

27 citations

Journal ArticleDOI
TL;DR: Results reveal that these eleven attributes helps the proposed approach to outperform over the other approaches such as LEACH, LEACH-C and EECS in terms of lifetime.
Abstract: Efficient utilization of power has recently emerged as a critical issue in sensor networks that is addressed by efficient clustering techniques. In WSN, clustering process selects cluster heads (CHs) to control the topology and consumes the power effectively. The comprehensive evolution of CH selection process increases the lifetime of sensor nodes resulting in total enhancement of the lifetime of WSN. The efficiency of clustering is affected by many attributes like higher residual energy, distance from a normal node to CH, distance from CH to the Base Station, etc. The conflicting nature of these attributes makes it difficult to find the cooperation among these attributes for optimal clustering. In this paper, we have applied MADM approaches for optimal CH selection to enhance the lifetime of WSN by utilizing eleven attributes, these attributes have very important role in efficient power consumption during data set collection. The MADM approaches employed for ranking and choosing optimal CHs are: Technique for Order Preference by Similarity to Ideal Solution, Preference Ranking Organization METHod for Enrichment Evaluations, and Analytic Hierarchy Process. Results reveal that these eleven attributes helps the proposed approach to outperform over the other approaches such as LEACH, LEACH-C and EECS in terms of lifetime.

27 citations

Journal ArticleDOI
TL;DR: A surface plasmon resonance (SPR) sensor that makes use of titanium/silver thin film on indium tin oxide (ITO) coated glass has been proposed in this article.
Abstract: We propose a surface plasmon resonance (SPR) sensor that makes use of titanium/silver thin film on indium tin oxide (ITO) coated glass. The use of silver enhances the detection accuracy of the sensor, whereas ITO coated glass results in good sensitivity. Fabrication and characterization of the sensor chip, i.e., ITO/Ti/Ag have been carried out. The effect of surface roughness on the performance of the sensor has been systematically studied. This paper reveals that for rough surface, the sensor performance degrades significantly and there is a need for optimization of the thickness of the top layer for the best performance of the sensor. Both experimental and simulation study have been carried out to substantiate the results.

27 citations

Journal ArticleDOI
TL;DR: The proposed FD-OTA with rail-to-rail linear input range operating in weak inversion region with fully differential class AB input and output structures has ensured increased gain, GBW, slew rates and output swings with reduced nonlinearity and common mode substrate noise.
Abstract: This paper presents a single-stage ultra-low-power fully differential operational transconductance amplifier (FD-OTA) with rail-to-rail linear input range operating in weak inversion region. The input core of the OTA is comprised of source degenerated, flipped voltage follower (FVF)-based bulk-driven class AB input pair, into which a regenerative feedback loop has been inserted to boost its bulk transconductance (gmb). The proposed FD-OTA has utilized self-cascode current mirror (SC-CM) loads, which increase its open loop gain from nominal intrinsic value of 42dB to 70.4dB. It has provided 9.24kHz gain bandwidth (GBW), consuming 64nW of quiescent power from a 0.51V single power supply at 15pF load. The proposed OTA in unity gain configuration has ensured reduced total harmonic distortion (THD) of −52.4dB at 200Hz frequency and 1Vp-p signal swing. Its fully differential class AB input and output structures have ensured increased gain, GBW, slew rates and output swings with reduced nonlinearity and common mode substrate noise. The Cadence Virtuoso environment using GPDK 180nm standard n-well CMOS process technology has been used to simulate the proposed circuit.

27 citations

Journal ArticleDOI
TL;DR: In this article, the effects of variation of ambient magnetic field, gravitational parameter and adiabatic exponent on the propagation of a cylindrical (or spherical) shock wave driven out by a piston moving with time according to an exponential law, in a self-gravitating ideal gas with azimuthal magnetic field is investigated.
Abstract: The propagation of a cylindrical (or spherical) shock wave driven out by a piston moving with time according to an exponential law, in a self-gravitating ideal gas with azimuthal magnetic field is investigated. The initial magnetic field is assumed to be varying according to an exponential law. Solutions are obtained for both the cases of isothermal and adiabatic flows. The effects of variation of ambient magnetic field, gravitational parameter and adiabatic exponent are worked out in detail. It is manifested that the increase in strength of ambient magnetic field has decaying effect on the shock wave however increase in the value of gravitational parameter has reverse effect on the shock strength. The compressibility of the medium is increased in the presence of gravitational field. Also, a comparison between the solutions obtained in the case of isothermal and adiabatic flows is done. Density, pressure, velocity and magnetic field increases, however mass decreases as we move inward from the shock front towards the piston.

27 citations


Authors

Showing all 2547 results

NameH-indexPapersCitations
Santosh Kumar80119629391
Anoop Misra7038517301
Naresh Kumar66110620786
Munindar P. Singh6258020279
Arvind Agarwal5832512365
Mahendra Kumar542169170
Jay Singh513018655
Lalit Kumar4738111014
O.N. Srivastava4754810308
Avinash C. Pandey453017576
Sunil Gupta435188827
Rakesh Mishra415457385
Durgesh Kumar Tripathi371335937
Vandana Singh351904347
Prashant K. Sharma341743662
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202342
202284
2021728
2020587
2019532
2018423