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Pankaj Kumar on Muck Rack

Pankaj Kumar

Delhi
As seen in: British Journal of Cancer, Nature, arXiv, Hindustan Times, MDPI, ZDNet, ACS Publications, Firstpost, Journal of Chemical & Engineering Data, McKinsey & Company and

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Pankaj Kumar’s Biography

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Acharya Pankaj Kumar is a very renowned and accomplished astrologer in India, and has been an expert on coming up with expert predictions for his clientele. He is very learned, and has immense knowledge in the field of Astrology, Lal kitab, Vastu Shastra, Feng-Shui, Pyra Vastu, Numerology and Gemology. He is committed to reach out to people who require expert advice on various aspects of their life, and is very professional when it comes to giving his clients the right piece of advice to help c…

Articles

Secrecy outage and capacity analysis for UAV-assisted IRS-aided G2G system

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By Nikita Goel, Pankaj Kumar, Sandesh Jain, Manoj Tolani, Swati Yadav, Sam Darshi
| Nature Verified
Abstract The integration of intelligent reflecting surfaces (IRS) with unmanned aerial vehicle (UAV) is rapidly emerging as a groundbreaking approach to enhancing the performance of 5G and beyond (5G+) wireless networks. This paper considers UAV-assisted-IRS-aided ground-to-ground (G2G) communication (UA-IRS-G2G) for improving the reliability of ground users (GUs) in infrastructure-less scenarios.
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Reducing computational complexity in nonlinear power system state estimation via ANN-assisted linear Kalman filtering

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By Sandip Chanda, Pankaj Kumar, Soham Dutta, Suvraujjal Dutta, Alok Kumar Shrivastav, Abhinandan De
| Nature Verified
Abstract This paper proposes a computationally efficient dynamic state estimation algorithm for nonlinear power networks using synchronized phasor measurements and a combination of an artificial neural network and a linear Kalman filter. The methodology involves using both the predicting abilities of the artificial neural network (ANN) and the iterative correction properties of the linear Kalman filter to estimate system states under dynamic operating conditions.
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A multimodal multi-label deep learning framework with temporal attention for detection of upper-limb motor activities for prosthetic control

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By Deepak Joshi, Rakesh Chandra Joshi, Pankaj Kumar, Santanu Mitra
| Nature Verified
Abstract Accurate detection of simultaneous grip and elbow flexion is critical for advanced rehabilitation monitoring, intuitive prosthetic control and human-machine interaction. Existing approaches, particularly those relying solely on surface electromyography (sEMG), often struggle to capture overlapping muscle activations and the biomechanical context of dynamic upper-limb movements.
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