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: A detailed survey on different solar forecasting techniques has been presented for precise energy estimates and a detailed study on energy efficient power management techniques is proposed to address the feasibility of energy‐harvesting approach in WSNs.
25 citations
TL;DR: In this article, a machine learning algorithm named Bernoulli's Naive Bayes Classifier, which is the extended version of Multinomial Naïve Bayes with predictors as Boolean variables was used to detect fake news.
25 citations
TL;DR: The zinc oxide (ZnO)-grafted polymers have emerged as a prominent material for fabrication of 3D printed biosensor due to its inherent antibacterial, antifungal, room temperature ferromagnetic magn...
Abstract: The zinc oxide (ZnO)-grafted polymers have emerged as a prominent material for fabrication of 3D printed biosensor due to its inherent antibacterial, antifungal, room temperature ferromagnetic magn...
25 citations
TL;DR: A detailed study of some of the techniques like RoF-PON networks, orthogonal frequency division multiplexing (OFDM), optical millimeter wave generation, Dense wave length division multipleXing (DWDM) has been done, suggesting the future scope of these technologies in the field of RoF communication systems.
25 citations
TL;DR: In this article, the authors proposed a smart system of air quality monitoring that help in preventing and controlling airborne allergies and reducing the burden of disease and the cost of treatment using meta-heuristic and machine learning algorithms.
Abstract: The air quality monitoring system systematically monitors the level of pollutants in the air by measuring the concentration of the particular pollutant in the surrounding and the outside environment. The strategy for developing the monitoring system should ensure the acceptable quality of data, to store and record the data in the database, the analysis of data and to present the result. In this concern, we have proposed a smart system of air quality monitoring that help in preventing and controlling airborne allergies and reducing the burden of disease and the cost of treatment. The healthcare data layers and healthcare APIs for standardizing the smart health predictive analytics were derived using meta-heuristic and Machine learning algorithms. This work mainly focused on improving the existing expert systems of air quality monitoring. In concern of this, the detail study of various terms related to air quality monitoring has been done and proposed a new approach that able to gives a better outcomes. In the proposed work, the meta-heuristic firefly optimization has been applied to optimize the selected features during feature selection process and then further classified by using support vector machine which predict the index level and gives better precision and recall of 95.7% and 93.1% respectively and accuracy of 94.4% while compare it with the existing approaches.
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 |