Zobrazeno 1 - 10
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pro vyhledávání: '"Kashif Muhammad"'
Autor:
Kashif Muhammad, Naz Sumaira, Zahoor Muhammad, Shah Syed Wadood Ali, Uddin Jalal, Esa Muhammad, ur Rashid Haroon, Ullah Riaz, Alotaibi Amal
Publikováno v:
Open Chemistry, Vol 22, Iss 1, Pp 36-50 (2024)
Externí odkaz:
https://doaj.org/article/076a5bc0c37543ddad1f2b4ed5cf0e05
Publikováno v:
Central European Management Journal, Vol 29, Iss 2, Pp 121-146 (2021)
Purpose: Drawing on social exchange theory (SET), this study explores the mediating role of quiescent silence as a link between organizational stressors and turnover intentions among Russian frontline employees (FLEs). Furthermore, we aim to investig
Externí odkaz:
https://doaj.org/article/2994d9ad36b14fb1ab0dd509b5cd81ec
Portfolio Optimization (PO) is a financial problem aiming to maximize the net gains while minimizing the risks in a given investment portfolio. The novelty of Quantum algorithms lies in their acclaimed potential and capability to solve complex proble
Externí odkaz:
http://arxiv.org/abs/2407.19857
Autor:
Zheng, Di, Kashif, Muhammad Fayyaz, Piscopo, Linda, Collard, Liam, Ciraci, Cristian, De Vittorio, Massimo, Pisanello, Ferruccio
Creating plasmonic nanoparticles on a tapered optical fiber tip enables a remote SERS sensing probe, ideal for challenging sampling scenarios like biological tissue, specific cells, on-site environmental monitoring, and deep brain structures. However
Externí odkaz:
http://arxiv.org/abs/2404.13695
Extended versions of the noncommutative(nc) KP equation and the nc mKP equation are constructed in a unified way, for which two types of quasideterminant solutions are also presented. In commutative setting, the quasideterminant solutions provide the
Externí odkaz:
http://arxiv.org/abs/2404.11391
Autor:
Zaman, Kamila, Ahmed, Tasnim, Kashif, Muhammad, Hanif, Muhammad Abdullah, Marchisio, Alberto, Shafique, Muhammad
In current noisy intermediate-scale quantum devices, hybrid quantum-classical neural networks (HQNNs) represent a promising solution that combines the strengths of classical machine learning with quantum computing capabilities. Compared to classical
Externí odkaz:
http://arxiv.org/abs/2402.10605
Autor:
Kashif, Muhammad, Shafique, Muhammad
In this paper, we present a novel framework for enhancing the performance of Quanvolutional Neural Networks (QuNNs) by introducing trainable quanvolutional layers and addressing the critical challenges associated with them. Traditional quanvolutional
Externí odkaz:
http://arxiv.org/abs/2402.09146
Publikováno v:
2024 International Joint Conference on Neural Networks (IJCNN)
In this paper, we conduct a comprehensively analyze the influence of different quantum noise gates, including Phase Flip, Bit Flip, Phase Damping, Amplitude Damping, and the Depolarizing Channel, on the performance of HyQNNs. Our results reveal disti
Externí odkaz:
http://arxiv.org/abs/2402.08523
Autor:
Kashif, Muhammad, Shafique, Muhammad
This paper delves into the intricate dynamics of quantum noise and its influence on the onset and mitigation of barren plateaus (BPs) - a phenomenon that critically impedes the scalability of QNNs. We find that BPs appear earlier in noisy quantum env
Externí odkaz:
http://arxiv.org/abs/2402.08475
Autor:
Temidayo O. Elufisan, Isabel C. Rodríguez-Luna, Omotayo Opemipo Oyedara, Alejandro Sánchez-Varela, Armando Hernández-Mendoza, Edgar Dantán Gonzalez, Alma D. Paz-González, Kashif Muhammad, Gildardo Rivera, Miguel Angel Villalobos-Lopez, Xianwu Guo
Publikováno v:
PeerJ, Vol 8, p e8102 (2020)
Background Stenotrophomonas are ubiquitous gram-negative bacteria, which can survive in a wide range of environments. They can use many substances for their growth and are known to be intrinsically resistant to many antimicrobial agents. They have be
Externí odkaz:
https://doaj.org/article/f143dcafc35d4051908d67193e70ad75