3,836 research outputs found
I Was Addicted to Sex With Married Women
No full textAs a young man, Akhil Sharma revelled in the most dangerous of liaisons, having sex with other men's wives – until the thrill began to pall
Maldives Resorts: Eco-Friendly Vacations
No full textLuxurious, exclusive and remote, the Maldives are the ultimate beach escape. They’re also a case study in the risks of global warming. Writer Akhil Sharma visits the country’s most eco-friendly resorts and discovers a remarkable cuisine worth protecting
Recollections of a Hindu Hedonist
No full textNovelist Akhil Sharma grew up in a teetotaling Indian household. Here, he tells how discovering a passion for great wine helped him create a new identity out of a painful past
MC2021 Submission: Narsimha
No full textSubmission to model counting competition 2021 for all the tracks by Mate Soos, Roland Yap, Shubham Sharma, Subhajit Roy, Yong Lai, Zhenghang, and Kuldeep S. Meel (NUS group). Narsimha is based on our probabilistic exact counter Ganak (https://github.com/meelgroup/ganak), exact model counter ExactMC (https://github.com/meelgroup/KCBox) and approximate model counter ApproxMC (https://github.com/meelgroup/approxmc)
Interview with Lakshmi Raj Sharma, Author of The Tailor’s Needle
No full textInterview with Indian writer Lakshmi Raj Sharma, author of 'The Tailor's needle
sj-docx-1-pie-10.1177_09544089231159834 - Supplemental material for Lean, green, and smart manufacturing: An ingenious framework for enhancing the sustainability of operations management on the shop floor in industry 4.0
No full textSupplemental material, sj-docx-1-pie-10.1177_09544089231159834 for Lean, green, and smart manufacturing: An ingenious framework for enhancing the sustainability of operations management on the shop floor in industry 4.0 by Varun Tripathi, Somnath Chattopadhyaya, A K Mukhopadhyay, Shubham Sharma, Vineet Kumar, Changhe Li and Sunpreet Singh in Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering</p
ROLE OF VARIOUS SEEDS IN THE TREATMENT OF POLYCYSTIC OVARIAN SYNDROME (PCOS)
No full textJobanpreet Kaur*, Himani Dhiman, Riya Thakur, Shubham Sharma andSonia Kau
Impact of authentic happiness on emotional intelligence among Indians in late adolescence
No full textDr. Savita K Tiwari , Shubham Sharma , Akshyata Ra
Sparse Channel Estimation for Visible Light Optical OFDM Systems Relying on Bayesian Learning
No full textSparse multipath channel impulse response (CIR) estimation schemes are conceived for optical orthogonal frequency division multiplexing (O-OFDM) visible light communication (VLC) systems. We commence by deriving the input-output models for both asymmetrically clipped optical OFDM (ACOOFDM) and direct current-biased optical OFDM (DCO-OFDM) systems. A multipath CIR model is derived that captures both the diffusive as well as specular reflections of the VLC channel. Next, we introduce both the sparsity-agnostic conventional least square (LS) and the linear minimum mean square error (LMMSE) channel estimation (CE) techniques. This is followed by the orthogonal matching pursuit (OMP)-based sparse recovery technique, which exploits the delay-domain sparsity of the CIR. Furthermore, a novel sparse multipath CIR estimation scheme is proposed using the Bayesian learning (BL) framework, which requires only a limited number of pilot subcarriers, hence resulting in a reduced pilot overhead as compared to other state-of-the-art (SoA) CE techniques. The Bayesian Cramer Rao lower bound (BCRLB) as well as the Oracle-minimum mean squared error (O-MMSE) estimator are also derived for benchmarking the estimation performance of the proposed BL-based framework. Our simulation results demonstrate that the proposed BL method outperforms other existing sparse and conventional CE methods in terms of various metrics, such as the normalized mean-square-error (NMSE), the outage probability (OP), and the bit error-rate (BER) despite its reduced pilot overhead
Efficient Computation for Localization and Navigation System for a Differential Drive Mobile Robot in Indoor and Outdoor Environments
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