Institution
Chandigarh University
Education•Mohali, India•
About: Chandigarh University is a education organization based out in Mohali, India. It is known for research contribution in the topics: Computer science & Chemistry. The organization has 1358 authors who have published 2104 publications receiving 10050 citations.
Papers
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TL;DR: Results indicate that SMC gives higher accuracy for spelling mistakes identification and correction for the commonly confused words as compared to other spelling correction algorithms.
26 citations
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TL;DR: This paper focuses on the comprehensive analysis of the effect of COVID-19 on Indian states and Union Territories and the development of a regression model to predict the number of discharge patients and deaths in each state.
Abstract: The COVID-19 disease has already spread to more than 213 countries and territories with infected (confirmed) cases of more than 27 million people throughout the world so far, while the numbers keep increasing In India, this deadly disease was first detected on January 30, 2020, in a student of Kerala who returned from Wuhan Because of India’s high population density, different cultures, and diversity, it is a good idea to have a separate analysis of each state Hence, this paper focuses on the comprehensive analysis of the effect of COVID-19 on Indian states and Union Territories and the development of a regression model to predict the number of discharge patients and deaths in each state The performance of the proposed prediction framework is determined by using three machine learning regression algorithms, namely Polynomial Regression (PR), Decision Tree Regression, and Random Forest (RF) Regression The results show a comparative analysis of the states and union territories having more than 1000 cases, and the trained model is validated by testing it on further dates The performance is evaluated using the RMSE metrics The results show that the Polynomial Regression with an RMSE value of 0 08, shows the best performance in the prediction of the discharged patients In contrast, in the case of prediction of deaths, Random Forest with a value of 0 14, shows a better performance than other techniques © 2021 Tech Science Press All rights reserved
25 citations
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15 May 2019TL;DR: This article clearly delivers a comprehensive analysis of services that aSMART City must provide in addition with a SMART city SMART Architecture.
Abstract: IoT is rebuilding and restructuring the nation with technological advancement with all set of Pros and Cons associated with the Technology. There has been much talk about ‘Smart’ or ‘intelligent’ cities these days. All around the world government organizations, administrators and technocrats are working as a team to design an intelligent city that will provide an easy and better life to the residents. Smart City Mission, is an urban renewal and retrofitting program by the Government of India with the mission to develop 100 cities across the country making them citizen friendly and sustainable. This article clearly delivers a comprehensive analysis of services that a SMART City must provide in addition with a SMART city SMART Architecture. In addition, we present current challenges and proposed technological solutions to the challenges. Finally the article delivers future research perspectives in the field of IoT.
25 citations
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TL;DR: In this article, the effect of initial concentration and contact time on arsenic and fluoride removal from groundwater was studied using anjili tree sawdust chemically modified by Ferric hydroxide and Activated Alumina (SFAA).
25 citations
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TL;DR: In this article, an interpenetrating polymer network (IPN) nanocomposite hydrogel based on gum acacia, acrylamide and acrylic acid Ga-cl-poly (AAm-IPN-AA) was synthesized by a two-step aqueous polymerization followed by a one-step impregnation of silver nanoparticles.
25 citations
Authors
Showing all 1533 results
Name | H-index | Papers | Citations |
---|---|---|---|
Neeraj Kumar | 76 | 587 | 18575 |
Rupinder Singh | 42 | 458 | 7452 |
Vijay Kumar | 33 | 147 | 3811 |
Radha V. Jayaram | 32 | 114 | 3100 |
Suneel Kumar | 32 | 180 | 5358 |
Amanpreet Kaur | 32 | 367 | 5713 |
Vikas Sharma | 31 | 145 | 3720 |
Munish Kumar Gupta | 31 | 192 | 3462 |
Vijay Kumar | 30 | 113 | 2870 |
Shashi Kant | 29 | 160 | 2990 |
Sunpreet Singh | 29 | 153 | 2894 |
Gagangeet Singh Aujla | 28 | 109 | 2437 |
Deepak Kumar | 28 | 273 | 2957 |
Dilbag Singh | 27 | 77 | 1723 |
Tejinder Singh | 27 | 162 | 2931 |