M
Muhammad Younas
Researcher at Oxford Brookes University
Publications - 351
Citations - 4071
Muhammad Younas is an academic researcher from Oxford Brookes University. The author has contributed to research in topics: Web service & Chemistry. The author has an hindex of 26, co-authored 269 publications receiving 3099 citations. Previous affiliations of Muhammad Younas include University of the Sciences & HITEC University.
Papers
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Journal ArticleDOI
Mobility Management Scheme for Context-Aware Transactions in Pervasive and Mobile Cyberspace
Muhammad Younas,Irfan Awan +1 more
TL;DR: A new mobility management scheme that ensures seamless connectivity and reliable execution of context-aware transactions during mobility of users is developed and designed and developed using a combination of different queuing models.
Journal Article
Chronic cadmium induced oxidative stress not the DNA fragmentation modulates growth in spring wheat (Triticum aestivum).
Sana Riaz,Muhammad Iqbal,Iqbal Hussain,Rizwan Rasheed,Muhammad Arslan Ashraf,Saqib Mahmood,Muhammad Younas,Mishal Iqbal +7 more
Journal ArticleDOI
Molybdenum-induced effects on leaf ultra-structure and rhizosphere phosphorus transformation in Triticum aestivum L.
Muhammad Shoaib Rana,Xuecheng Sun,Muhammad Imran,Shafaqat Ali,Muhammad Shaaban,Mohamed G. Moussa,Zaid Khan,Javaria Afzal,Rana Binyamin,Parashuram Bhantana,Mufid Alam,Intisar Ud Din,Muhammad Younas,Chengxiao Hu +13 more
TL;DR: Molybdenum (Mo) supply increased plant biomass, grain yield, P uptake, preserved the configuration of chloroplast, stomata, and mesophyll tissue cells, suggesting the complementary effects of Mo on wheat yield and P accumulation.
Journal ArticleDOI
Effects of population size for location-aware node placement in WMNs: evaluation by a genetic algorithm--based approach
TL;DR: This paper used a location-aware node placement of mesh router in cells of considered grid area to maximize network connectivity and user coverage and evaluates the performance of the proposed and implemented WMN-GA system for low and high density of clients considering different distributions and considering giant component and number of covered users parameters.