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您的检索式：作者名="Fayaz ASAD"
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| 1 | Temperature variability in northern Iran during the past 700 years显示文摘Warming is significantly affecting ecosystems in dry-warm areas,such as the Middle East[1],but long-term climatic records are often scarce in these regions.One important proxy source of climate data is tree rings,which have contributed to understanding climate changes over the past millennium[1].Under the PAGES2K framework[2],a tree-ring network of the Eurasian continent | Vilma Bayramzadeh Haifeng Zhu Xiaoming Lu Pedram Attarod Hui Zhang Xiaoxia Li Fayaz Asad Eryuan Hang | 2018 | Science Bulletin2018，63，8： | 3 |
| 2 | Tree ring derived summer temperature variability over the past millennium in the western Himalayas of northern Pakistan显示文摘Long-term high resolution climate proxies are essential for understanding climate variability particularly,in regions such as the western Himalayas of northern Pakistan,where few long-term climate records are available.Using standard dendrochronological methods,an 1132-year(882 to 2013 C.E.)tree-ring chronology of Juniperus excelsa M.Bieb was established from the western Himalayas,northern Pakistan(WHNP).Tree growth was negatively and significantly(r=-0.65)correlated with the growing season(June-July)mean temperature,and positively and weakly(r=0.22)associated with precipitation.This inverse relationship of tree radial growth with temperature and positive association with precipitation demonstrated that forest growth is sensitive to high temperature related drought.Utilizing a reliable STD chronology and robust reconstruction model,a 928-year(1086 to 2013 C.E.)mean temperature reconstruction was developed for the WHNP using the substantial negative correlation between the summer temperature and standard tree ring-width chronology.According to statistical validation,the reconstruction accounted for 41.6% of the climatic variation for the period of 1956-2013 C.E.instrumental period.Individual extreme-warm periods occurred in 1093 C.E.(29.42℃)and extreme cold periods in 1088 C.E.(26.99℃)observed during the past 928 years.The reconstruction's multi-taper method(MTM)spectral analysis reveals significant(p<0.05)2-3-year and 63.8-year cycles.Since the 2-3-year cycle occurred within the range of ENSO variation,which indicates that ENSO had an impact on the regional temperature in our studied area. | Fayaz ASAD Haifeng ZHU Tabassum YASEEN Ru HUANG Mukund Palat RAO | 2023 | Frontiers of Earth Science2023，17，4： | 0 |
| 3 | Application of the Deep Convolutional Neural Network for the Classification of Auto Immune Diseases显示文摘IIF(Indirect Immune Florescence)has gained much attention recently due to its importance in medical sciences.The primary purpose of this work is to highlight a step-by-step methodology for detecting autoimmune diseases.The use of IIF for detecting autoimmune diseases is widespread in different medical areas.Nearly 80 different types of autoimmune diseases have existed in various body parts.The IIF has been used for image classification in both ways,manually and by using the Computer-Aided Detection(CAD)system.The data scientists conducted various research works using an automatic CAD system with low accuracy.The diseases in the human body can be detected with the help of Transfer Learning(TL),an advanced Convolutional Neural Network(CNN)approach.The baseline paper applied the manual classification to the MIVIA dataset of Human Epithelial cells(HEP)type II cells and the Sub Class Discriminant(SDA)analysis technique used to detect autoimmune diseases.The technique yielded an accuracy of up to 90.03%,which was not reliable for detecting autoimmune disease in the mitotic cells of the body.In the current research,the work has been performed on the MIVIA data set of HEP type II cells by using four well-known models of TL.Data augmentation and normalization have been applied to the dataset to overcome the problem of overfitting and are also used to improve the performance of TL models.These models are named Inception V3,Dens Net 121,VGG-16,and Mobile Net,and their performance can be calculated through parameters of the confusion matrix(accuracy,precision,recall,and F1 measures).The results show that the accuracy value of VGG-16 is 78.00%,Inception V3 is 92.00%,Dense Net 121 is 95.00%,and Mobile Net shows 88.00%accuracy,respectively.Therefore,DenseNet-121 shows the highest performance with suitable analysis of autoimmune diseases.The overall performance highlighted that TL is a suitable and enhanced technique compared to its counterparts.Also,the proposed technique is used to detect autoimmune diseases with a minimal margin of errors and flaws. | Fayaz Muhammad Jahangir Khan Asad Ullah Fasee Ullah Razaullah Khan Inayat Khan Mohammed ElAffendi Gauhar Ali | 2023 | Computers, Materials & Continua2023，77，10： | 0 |
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