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| 1 | 腐植酸施用方法对绿豆产量及其构成因子的影响显示文摘为了探索腐植酸(HA)的施用方法,在白沙瓦开伯尔-普什图省农业大学的农业研究农场内进行了完全随机区组设计试验,并设置3次重复。HA的施用方法分为浸种、叶片喷施和土壤施用3种。HA的施用方法对绿豆单株结荚数、每荚粒数、千粒重和籽粒产量具有显著影响,而对绿豆生物量影响不大。每公顷土地施用3 kg HA能显著提高绿豆结荚率、千粒重和产量;而土壤中加入1 kg/hm^2和2 kg/hm^2 HA,浓度为0、1%、2%的HA浸种和0.01%、0.05%、0.1%的HA叶面喷施3种方法所得到的结果在统计学上相似。由此得出结论:3种施用HA的方法均能显著提高绿豆产量及其构成因子。 | Muhammad Waqas Bashir Ahmad Muhammad Arif Fazal Munsif Abdul Latif Khan Muhammad Amin Sang-Mo Kang Yoon-Ha Kim In-Jung Lee 刘雪娇 茹雪峰 高同国 | 2016 | 腐植酸2016，，6： | 2 |
| 2 | 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 |
| 3 | Deepdive:a learning-based approach for virtual camera in immersive contents显示文摘A 360°video stream provide users a choice of viewing one's own point of interest inside the immersive contents.Performing head or hand manipulations to view the interesting scene in a 360°video is very tedious and the user may view the interested frame during his head/hand movement or even lose it.While automatically extracting user's point of interest(UPI)in a 360°video is very challenging because of subjectivity and difference of comforts.To handle these challenges and provide user's the best and visually pleasant view,we propose an automatic approach by utilizing two CNN models:object detector and aesthetic score of the scene.The proposed framework is three folded:pre-processing,Deepdive architecture,and view selection pipeline.In first fold,an input 360°video-frame is divided into three sub frames,each one with 120°view.In second fold,each sub-frame is passed through CNN models to extract visual features in the sub-frames and calculate aesthetic score.Finally,decision pipeline selects the sub frame with salient object based on the detected object and calculated aesthetic score.As compared to other state-of-the-art techniques which are domain specific approaches i.e.,support sports 360°video,our syste m support most of the 360°videos genre.Performance evaluation of proposed framework on our own collected data from various websites indicate performance for different categories of 360°videos. | Muhammad IRFAN Muhammad MUNSIF | 2022 | Virtual Reality & Intelligent Hardware2022，4，3： | 1 |
| 4 | Integrated use of organic manures and inorganic fertilizers for the cultivation of lowland rice in Pakistan显示文摘 | Muhammad SharifZia Muhammad Munsif Muhammad Aslam | 1992 | Soll sci plant nutr1992，38，2： | 1 |
| 5 | 水稻花粉小肽锌指蛋白基因OsFLZ13功能研究显示文摘FCS样锌指蛋白(FLZ)与植物的生长发育和逆境胁迫反应相关。水稻的FLZ基因家族分析和功能研究较少。本研究利用TBtools对水稻基因组Blast,鉴定到29个OsFLZ家族基因成员,并分析了相关基因位置、基因结构、motif和启动子顺式作用元件等特征。随后,通过水稻CREP数据库研究了FLZ家族成员的全生育期组织表达模式,并发现其中的OsFLZ13基因在开花前的花药中特异高水平表达。随后β-D-葡萄糖苷酸酶(GUS)染色显示,OsFLZ13在花药发育的第8阶段开始表达,并在开花前的第14阶段表达量最高。用CRISPR/Cas9基因编辑获得的突变体植株结实率显著下降。相比野生型中花11的94%结实率,Osflz13-1和Osflz13-2的结实率分别只有44%和36%。本研究表明OsFLZ13参与花药发育以及花粉育性的调控,为进一步研究该基因及其家族基因的功能提供参考,同时对水稻雄性不育利用具有潜在的价值。 | 张丽洁 周海宇 MUHAMMAD Zeshan MUNSIF Ali Shad 杨明冲 李波 韩世健 张翠翠 胡利华 王令强 | 2024 | 作物学报2024，50，3： | 0 |
| 6 | CT-NET: A Novel Convolutional Transformer-Based Network for Short-Term Solar Energy Forecasting Using Climatic Information显示文摘Photovoltaic(PV)systems are environmentally friendly,generate green energy,and receive support from policies and organizations.However,weather fluctuations make large-scale PV power integration and management challenging despite the economic benefits.Existing PV forecasting techniques(sequential and convolutional neural networks(CNN))are sensitive to environmental conditions,reducing energy distribution system performance.To handle these issues,this article proposes an efficient,weather-resilient convolutional-transformer-based network(CT-NET)for accurate and efficient PV power forecasting.The network consists of three main modules.First,the acquired PV generation data are forwarded to the pre-processing module for data refinement.Next,to carry out data encoding,a CNNbased multi-head attention(MHA)module is developed in which a single MHA is used to decode the encoded data.The encoder module is mainly composed of 1D convolutional and MHA layers,which extract local as well as contextual features,while the decoder part includes MHA and feedforward layers to generate the final prediction.Finally,the performance of the proposed network is evaluated using standard error metrics,including the mean squared error(MSE),root mean squared error(RMSE),and mean absolute percentage error(MAPE).An ablation study and comparative analysis with several competitive state-of-the-art approaches revealed a lower error rate in terms of MSE(0.0471),RMSE(0.2167),and MAPE(0.6135)over publicly available benchmark data.In addition,it is demonstrated that our proposed model is less complex,with the lowest number of parameters(0.0135 M),size(0.106 MB),and inference time(2 ms/step),suggesting that it is easy to integrate into the smart grid. | Muhammad Munsif Fath U Min Ullah Samee Ullah Khan Noman Khan Sung Wook Baik | 2023 | Computer Systems Science & Engineering2023，47，11： | 0 |
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