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您的检索式：作者名="Mohib Ullah"
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| 1 | Serious games in science education:a systematic literature review显示文摘Teaching science through computer games,simulations,and artificial intelligence(AI)is an increasingly active research field.To this end,we conducted a systematic literature review on serious games for science education to reveal research trends and patterns.We discussed the role of virtual reality(VR),AI,and augmented reality(AR)games in teaching science subjects like physics.Specifically,we covered the research spanning between 2011 and 2021,investigated country-wise concentration and most common evaluation methods,and discussed the positive and negative aspects of serious games in science education in particular and attitudes towards the use of serious games in education in general. | Mohib ULLAH Sareer Ul AMIN Muhammad MUNSIF Muhammad Mudassar YAMIN Utkurbek SAFAEV Habib KHAN Salman KHAN Habib ULLAH | 2022 | Virtual Reality & Intelligent Hardware2022，4，3： | 2 |
| 2 | An update on the maize zein-gene family in the post-genomics era显示文摘Maize(Zea mays)is a cereal crop of global food importance.However,the deficiency of essential amino acids,more importantly lysine,methionine and tryptophan,in the major seed storage zein proteins makes corn nutritionally of low value for human consumption.The idea of improving maize nutritional value prompted the search for maize natural mutants harboring low zein contents and higher amount of lysine.These studies resulted in the identification of more than dozens of maize opaque mutants in the previous few decades,o2 mutant being the most extensively studied one.However,the high lysine contents but soft kernel texture and chalky endosperm halted the widespread application and commercial success of maize opaque mutants,which ultimately paved the way for the development of Quality Protein Maize(QPM)by modifying the soft endosperm of o2 mutant into lysine-rich hard endosperm.The previous few decades have witnessed a marked progress in maize zein research.It includes elucidation of molecular mechanism underlying the role of different zein genes in seed endosperm development by cloning different components of zein family,exploring the general organization,function and evolution of zein family members within maize species and among other cereals,and elucidating the cis-and trans-regulatory elements modulating the regulation of different molecular players of maize seed endosperm development.The current advances in high quality reference genomes of maize lines B73 and Mo17 plus the completion of ongoing pan genome sequencing projects of more maize lines with NGS technologies are expected to revolutionize maize zein gene research in near future.This review highlights the recent advances in QPM development and its practical application in the post genomic era,genomic and physical composition and evolution of zein family,and expression,regulation and downstream role of zein genes in endosperm development.Moreover,recent genomic tools and methods developed for functional validation of maize zein genes are also discussed. | Nasr Ullah Khan Mohamed Sheteiwy Ning Lihua Muhammad Mohib Ullah Khan Zhao Han | 2019 | Food Production, Processing and Nutrition2019，1，1： | 0 |
| 3 | Robust Counting in Overcrowded Scenes Using Batch-Free Normalized Deep ConvNet显示文摘The analysis of overcrowded areas is essential for flow monitoring,assembly control,and security.Crowd counting’s primary goal is to calculate the population in a given region,which requires real-time analysis of congested scenes for prompt reactionary actions.The crowd is always unexpected,and the benchmarked available datasets have a lot of variation,which limits the trained models’performance on unseen test data.In this paper,we proposed an end-to-end deep neural network that takes an input image and generates a density map of a crowd scene.The proposed model consists of encoder and decoder networks comprising batch-free normalization layers known as evolving normalization(EvoNorm).This allows our network to be generalized for unseen data because EvoNorm is not using statistics from the training samples.The decoder network uses dilated 2D convolutional layers to provide large receptive fields and fewer parameters,which enables real-time processing and solves the density drift problem due to its large receptive field.Five benchmark datasets are used in this study to assess the proposed model,resulting in the conclusion that it outperforms conventional models. | Sana Zahir Rafi Ullah Khan Mohib Ullah Muhammad Ishaq Naqqash Dilshad Amin Ullah Mi Young Lee | 2023 | Computer Systems Science & Engineering2023，46，9： | 0 |
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