Institution
Techno India
About: Techno India is a based out in . It is known for research contribution in the topics: Computer science & Cloud computing. The organization has 4724 authors who have published 4005 publications receiving 34112 citations.
Topics: Computer science, Cloud computing, Wireless sensor network, Deep learning, Ultimate tensile strength
Papers published on a yearly basis
Papers
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28 Jul 2020
TL;DR: This work classifies offline three‐organized CBM with floats of ideas and awkwardness data, using an improved Dynamic AdaBoost for preparing a group classifier and an enhanced linear four rates (LFR) methodology is used by the classifier of nominal and continuous with synthetic minority oversampling technique (SMOTE) method.
Abstract: Nowadays, countless industrial IIoT contraptions and sensors are conveyed a sharp plant to gather tremendous information regarding system conditions and a computerized bodily framework for handling industrial plant's mist point of convergence by using keen assembling projects. By then, the system utilizes an array of condition‐based support model (CBM) procedures to predict when devices begin to unusually work and to keep them up or supplant their fragments ahead of time to avoid assembling colossal investigator items in smart manufacturing industries. CBM experiences problems of floating ideas (ie, conveying examples of deficiencies can change extra time) and information of lop‐sidedness (ie, information with issues represents a minority of all things considered). The condition‐based support assisted learning technique by the group that coordinates the assorted variety of numerous classifiers provides an elite response to address these issues. Therefore, in this work the proposed work classifies offline three‐organized CBM with floats of ideas and awkwardness data, using an improved Dynamic AdaBoost for preparing a group classifier and an enhanced linear four rates (LFR) methodology is used by the classifier of nominal and continuous (NC) with synthetic minority oversampling technique (SMOTE) method to tackle inconsistent information in recognizing concept floats in lop‐sidedness information. The investigational results scheduled datasets by varying notches anomaly demonstration that the future strategy has a high degree of accuracy in the identifiable evidence of minority knowledge, which is over 96%.
16 citations
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TL;DR: In this article, the silane functionalized MnO2 nanoparticles were incorporated in polythiophene (PT) to produce PT/silanes/MnO2 nanocomposites.
16 citations
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TL;DR: A simulation design of common BMS for four different batteries namely Nickel-Metal-Hydride, Nickel-Cadmium, Lithium-Ion and Lead-Acid is proposed and analysed using MATLAB/Simulink.
16 citations
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TL;DR: In this article, a combined integration of partially hydrolysed guar gum (PHGG) and orange peel fibre (OPF) into low-fat, set-type yogurt was explored.
16 citations
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TL;DR: A new immobilization support for the preparation of enzyme membrane in the presence of organic solvents with enzyme immobilized by entrapment technique has a long life due to its hydrophobic nature, as compared with other membranes.
Abstract: The present study describes a new immobilization support for the preparation of enzyme membrane in the presence of organic solvents. The support was composed of Formvar solubilization in organic solvents with enzyme. More than 90% of the enzyme was immobilized on the membrane. The membrane was prepared by mixing 4% Formvar in organic solvents and 1% cholesterol oxidase was immobilized by entrapment technique. Practically no leaching of the entrapped enzyme was observed. The resultant immobilized enzyme membrane was stored at 4 °C for 10 days without losing its activity. The pH and temperature stabilities were greater than those of the native enzyme. The immobilized enzyme membrane has a long life due to its hydrophobic nature, as compared with other membranes.
16 citations
Authors
Showing all 4724 results
Name | H-index | Papers | Citations |
---|---|---|---|
Subir Sarkar | 149 | 1542 | 144614 |
Anil Kumar | 99 | 2124 | 64825 |
Gajendra P. S. Raghava | 66 | 326 | 16671 |
Raj Jain | 64 | 424 | 30018 |
James D. Herbsleb | 58 | 174 | 17862 |
Bhalchandra M. Bhanage | 55 | 550 | 12500 |
Panniyammakal Jeemon | 54 | 135 | 58676 |
Sandeep Singh | 52 | 670 | 11566 |
Bidyut B. Chaudhuri | 51 | 368 | 11368 |
Donald R. Baer | 51 | 244 | 10679 |
Chandra P. Sharma | 48 | 325 | 12100 |
Ravi Kumar | 48 | 719 | 10970 |
Nilanjan Dey | 48 | 475 | 9160 |
K. P. Ramesh | 47 | 391 | 7504 |
Sunil Luthra | 45 | 162 | 6485 |