M
Muhammad Irfan
Researcher at Najran University
Publications - 928
Citations - 10675
Muhammad Irfan is an academic researcher from Najran University. The author has contributed to research in topics: Medicine & Biology. The author has an hindex of 36, co-authored 646 publications receiving 6333 citations. Previous affiliations of Muhammad Irfan include Pakistan Council of Scientific and Industrial Research & American University of Sharjah.
Papers
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Investigation of near-infrared luminescence in Er 3+ and Er 3+ /Yb 3+ co-doped ZnMgAl 10 O 17 phosphors
TL;DR: In this article, a combustion method was used for the preparation of ZnMgAl10O17-phosphor samples doped with Er3+ ions and codoped with both Er3 and Yb3+ ion.
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The reduced weak links in Cu0.5Tl0.5Ba2Ca4−xMgxCu5O14−δ (x = 1, 2 and 3) superconductors
Nawazish A. Khan,Muhammad Irfan +1 more
TL;DR: In this article, the weak link behavior of oxide superconductors has been studied from the width and peak temperature of the out-of-phase component of magnetic susceptibility ( χ ).
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Savior: A Reliable Fault Resilient Router Architecture for Network-on-Chip
Ayaz Hussain,Muhammad Irfan,Naveed Khan Baloch,Umar Draz,Tariq Ali,Adam Glowacz,Larisa Dunai,Jose A. Antonino-Daviu +7 more
TL;DR: This paper proposes a mechanism that can tolerate permanent faults that occur in the router and exploits the fault-tolerant techniques of resource sharing and paring between components for the input port unit and routing computation (RC) unit, the resource borrowing for virtual channel allocator (VA) and multiple paths for switch allocator and crossbar (XB).
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Influence of Superheated Vapour in Organic Rankine Cycles with Working Fluid R123 Utilizing Low-Temperature Geothermal Resources
Totok Prasetyo,Mochamad Denny Surindra,Wahyu Caesarendra,Taufik,Adam Glowacz,Muhammad Irfan,W. Głowacz +6 more
TL;DR: An experimental study on a binary cycle, applying R123 as the working fluid, to investigate the effect of variation in superheated vapour degree on the ORC efficiency and found that the magnitude of the mass flow rate affects the behaviour of the components of the OrC system.
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Computer Aided COVID-19 Diagnosis in Pandemic Era Using CNN in Chest X-ray Images
Ali Alqahtani,Mirza Mumtaz Zahoor,Rimsha Nasrullah,Aqil Fareed,Ahmad Afzaal Cheema,Abdullah Shahrose,Muhammad Irfan,Abdulmajeed Alqhatani,Abdulaziz A. Alsulami,Maryam Zaffar,Saifur Rahman +10 more
TL;DR: This work developed a novel computationally light and optimized deep Convolutional Neural Networks (CNNs) based framework for chest X-ray analysis and proposed a new COV-Net to learn COVID-specific patterns fromchest X-rays and employed several machine learning classifiers to enhance the discrimination power of the presented framework.