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: Materials science & Computer science. The organization has 1358 authors who have published 2104 publications receiving 10050 citations.
Papers
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TL;DR: In this article, PACT@γ-Fe2O3 was synthesized via oxidative free radical polymerization of acrylamide monomer in presence of γ-Fe 2O3 nanoparticles as a filler by grafting with chitosan biopolymer.
45 citations
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TL;DR: A broad overview of the progress of immunotherapy-based treatments and discuss future opportunities for their use in triple negative breast cancers (TNBCs) is provided in this paper, where the authors also discuss the potential for using immunotherapy in TNBCs.
44 citations
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TL;DR: This paper proposes an approach that devises a new hybrid technique, which is a combination of Maximum Likelihood Estimation (MLE) and Self Cancellation (SC) techniques through wavelet implication, to enhance BER performance of the OFDM system.
44 citations
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01 Aug 2021
TL;DR: This article proposes energy efficient optimal parent selection in RPL (EEOPS‐RPL) using firefly optimization algorithm to extend the lifespan of the IoT network.
Abstract: Energy conservation is a major challenge in the Internet of Things (IoT) as the number of resource‐constrained devices is connected to the network. Routing plays a vital role in IoT to ext...
44 citations
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02 Jul 2020TL;DR: To prove the effectiveness, K-NN algorithms and collaborative filtering are used to mainly focus on enhancing the accuracy of results as compared to content-based filtering, based on cosine similarity using k-nearest neighbor with the help of a collaborative filtering technique.
Abstract: Movies are one of the sources of entertainment, but the problem is in finding the desired content from the ever-increasing millions of content every year. However, recommendation systems come much handier in these situations. The aim of this paper is to improve the accuracy and performance of a regular filtering technique. Although varieties of methods are used to implement a recommendation system, Content-based filtering is the simplest method. Which takes input from the users, rechecks his/her history/past behavior, and recommends a list of similar movies. In this paper, to prove the effectiveness, K-NN algorithms and collaborative filtering are used to mainly focus on enhancing the accuracy of results as compared to content-based filtering. This approach is based on cosine similarity using k-nearest neighbor with the help of a collaborative filtering technique, at the same time removing the drawbacks of the content-based filtering. Although using Euclidean distance is preferred, cosine similarity is used as the accuracy of cosine angle and the equidistance of movies remain almost the same.
43 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 |