The quick spread of the CoronavirusDisease(COVID-19)infection around the world considered a real danger for global health.The biological structure and symptoms of COVID-19 are similar to other viral chest maladies,whi...The quick spread of the CoronavirusDisease(COVID-19)infection around the world considered a real danger for global health.The biological structure and symptoms of COVID-19 are similar to other viral chest maladies,which makes it challenging and a big issue to improve approaches for efficient identification of COVID-19 disease.In this study,an automatic prediction of COVID-19 identification is proposed to automatically discriminate between healthy and COVID-19 infected subjects in X-ray images using two successful moderns are traditional machine learning methods(e.g.,artificial neural network(ANN),support vector machine(SVM),linear kernel and radial basis function(RBF),k-nearest neighbor(k-NN),Decision Tree(DT),andCN2 rule inducer techniques)and deep learningmodels(e.g.,MobileNets V2,ResNet50,GoogleNet,DarkNet andXception).A largeX-ray dataset has been created and developed,namely the COVID-19 vs.Normal(400 healthy cases,and 400 COVID cases).To the best of our knowledge,it is currently the largest publicly accessible COVID-19 dataset with the largest number of X-ray images of confirmed COVID-19 infection cases.Based on the results obtained from the experiments,it can be concluded that all the models performed well,deep learning models had achieved the optimum accuracy of 98.8%in ResNet50 model.In comparison,in traditional machine learning techniques, the SVM demonstrated the best result for an accuracy of 95% and RBFaccuracy 94% for the prediction of coronavirus disease 2019.展开更多
In this work,By using the laser ablation technique(PLAL)to fabricate novel PMMA/G/Ag nanocomposites with less laser energy and short time ablation and study the structural,morphological and optical properties.The X-ra...In this work,By using the laser ablation technique(PLAL)to fabricate novel PMMA/G/Ag nanocomposites with less laser energy and short time ablation and study the structural,morphological and optical properties.The X-ray diffraction(XRD)confirmed that the GNPs and AgNPs in the PMMA matrix have a crystallite size increased with increasing the pulse number.Also,the SEM images confirm the homogeneous distribution of the GNPs and AgNPs in the PMMA matrix and the sizes of particles in the nanoscale.Additionally,the link between GNPs and AgNPs in the polymer matrix has been confirmed by the FTIR.Moreover,UV-VIS spectroscopy was studied and confirm the nanocomposite has optical properties with the presence of the polymer as a host and calculating the optical energy gap.For that,this novel nanocomposite with these properties promising for many applications.Finally,the study proved that the PLAL is very suitable for decorated graphene and metal on the polymer matrix with lower pulse laser energy and short ablation time.展开更多
Strain sensors have spread at present times,and their electrical resistance has been interpreted.In reality,the use of strain sensors has broadened the reach of technology and allowed us to track changes in the enviro...Strain sensors have spread at present times,and their electrical resistance has been interpreted.In reality,the use of strain sensors has broadened the reach of technology and allowed us to track changes in the environment in various ways.In recent years,due to their distinctive properties,films based on advanced carbon nanomaterials have started applying sophistication sensing.The strength of the tailored material has been obtained in addition to the various functions applied to these nanomaterials due to the particular structure of the nanomaterials.A prime catalyst for developing nanoscale sensors was this excellent feature.Carbon nanomaterials-based films have been increasing widely due to the excellent properties of nanocomposite-based films for sensing applications(piezoelectric application).There is also an instinctive structure of nanomaterials so that the material is high.Carbon nanomaterials such as graphene are now an excellent alternative for the production of sensors for thermal,electric and mechanical reading.展开更多
文摘The quick spread of the CoronavirusDisease(COVID-19)infection around the world considered a real danger for global health.The biological structure and symptoms of COVID-19 are similar to other viral chest maladies,which makes it challenging and a big issue to improve approaches for efficient identification of COVID-19 disease.In this study,an automatic prediction of COVID-19 identification is proposed to automatically discriminate between healthy and COVID-19 infected subjects in X-ray images using two successful moderns are traditional machine learning methods(e.g.,artificial neural network(ANN),support vector machine(SVM),linear kernel and radial basis function(RBF),k-nearest neighbor(k-NN),Decision Tree(DT),andCN2 rule inducer techniques)and deep learningmodels(e.g.,MobileNets V2,ResNet50,GoogleNet,DarkNet andXception).A largeX-ray dataset has been created and developed,namely the COVID-19 vs.Normal(400 healthy cases,and 400 COVID cases).To the best of our knowledge,it is currently the largest publicly accessible COVID-19 dataset with the largest number of X-ray images of confirmed COVID-19 infection cases.Based on the results obtained from the experiments,it can be concluded that all the models performed well,deep learning models had achieved the optimum accuracy of 98.8%in ResNet50 model.In comparison,in traditional machine learning techniques, the SVM demonstrated the best result for an accuracy of 95% and RBFaccuracy 94% for the prediction of coronavirus disease 2019.
文摘In this work,By using the laser ablation technique(PLAL)to fabricate novel PMMA/G/Ag nanocomposites with less laser energy and short time ablation and study the structural,morphological and optical properties.The X-ray diffraction(XRD)confirmed that the GNPs and AgNPs in the PMMA matrix have a crystallite size increased with increasing the pulse number.Also,the SEM images confirm the homogeneous distribution of the GNPs and AgNPs in the PMMA matrix and the sizes of particles in the nanoscale.Additionally,the link between GNPs and AgNPs in the polymer matrix has been confirmed by the FTIR.Moreover,UV-VIS spectroscopy was studied and confirm the nanocomposite has optical properties with the presence of the polymer as a host and calculating the optical energy gap.For that,this novel nanocomposite with these properties promising for many applications.Finally,the study proved that the PLAL is very suitable for decorated graphene and metal on the polymer matrix with lower pulse laser energy and short ablation time.
文摘Strain sensors have spread at present times,and their electrical resistance has been interpreted.In reality,the use of strain sensors has broadened the reach of technology and allowed us to track changes in the environment in various ways.In recent years,due to their distinctive properties,films based on advanced carbon nanomaterials have started applying sophistication sensing.The strength of the tailored material has been obtained in addition to the various functions applied to these nanomaterials due to the particular structure of the nanomaterials.A prime catalyst for developing nanoscale sensors was this excellent feature.Carbon nanomaterials-based films have been increasing widely due to the excellent properties of nanocomposite-based films for sensing applications(piezoelectric application).There is also an instinctive structure of nanomaterials so that the material is high.Carbon nanomaterials such as graphene are now an excellent alternative for the production of sensors for thermal,electric and mechanical reading.
