Medical image super-resolution is a fundamental challenge due to absorption and scattering in tissues.These challenges are increasing the interest in the quality of medical images.Recent research has proven that the r...Medical image super-resolution is a fundamental challenge due to absorption and scattering in tissues.These challenges are increasing the interest in the quality of medical images.Recent research has proven that the rapid progress in convolutional neural networks(CNNs)has achieved superior performance in the area of medical image super-resolution.However,the traditional CNN approaches use interpolation techniques as a preprocessing stage to enlarge low-resolution magnetic resonance(MR)images,adding extra noise in the models and more memory consumption.Furthermore,conventional deep CNN approaches used layers in series-wise connection to create the deeper mode,because this later end layer cannot receive complete information and work as a dead layer.In this paper,we propose Inception-ResNet-based Network for MRI Image Super-Resolution known as IRMRIS.In our proposed approach,a bicubic interpolation is replaced with a deconvolution layer to learn the upsampling filters.Furthermore,a residual skip connection with the Inception block is used to reconstruct a high-resolution output image from a low-quality input image.Quantitative and qualitative evaluations of the proposed method are supported through extensive experiments in reconstructing sharper and clean texture details as compared to the state-of-the-art methods.展开更多
This paper introduces the process of making 3D vector scenograph of an ancient building with large quantities of data with the aid of AutoCAD,which displays the effect of scenery drawings.The vital skills and techniqu...This paper introduces the process of making 3D vector scenograph of an ancient building with large quantities of data with the aid of AutoCAD,which displays the effect of scenery drawings.The vital skills and technique involved are illustrated through the example of Pagoda of Thousands of Buddha in Chi Lin Nunnery in HongKong.This construction was started in 1996 and finished in 1999 with the concrete structure internal and wood external,imitating the style of buildings in Tang Dynasty.Thus,3D vector scenograph become available to users.展开更多
Rechargeable aqueous Zn-ion batteries (ZIBs) have attracted great attention due to their costeffectiveness,high safety,and environmental friendliness.However,some issues associated with poor structural instability of ...Rechargeable aqueous Zn-ion batteries (ZIBs) have attracted great attention due to their costeffectiveness,high safety,and environmental friendliness.However,some issues associated with poor structural instability of cathode materials and fast self-discharge hinder the further development of ZIBs.Herein,a new configuration is introduced by placing a reduced graphene oxide film as a block layer between the separator and the V2O5·nH2O cathode.This layer prevents the free diffusion of dissolved active materials to the anode and facilitates the transport of Zn ion and electrons,largely improving the cyclic stability and alleviating the self-discharge.Accordingly,the optimized battery delivers a remarkable capacity of 191 mAh g^-1 after 500 cycles at 2 A g^-1.Moreover,a high capacity of 106 mAh g^-1 is achieved after 100 cycles at-20℃.The strategy proposed is expected to be applicable to other electrode systems,thus offering a new approach to circumvent the critical challenges facing aqueous batteries.展开更多
以分组密码扩散层为研究对象,根据轻量级分组密码的特点,基于2种密码结构构造轻量级扩散层,分别是基于Feistel结构构造面向软件实现的扩散层和基于LFSR构造面向硬件实现的扩散层。利用三轮Feistel结构,轮函数采用基于循环移位和异或的...以分组密码扩散层为研究对象,根据轻量级分组密码的特点,基于2种密码结构构造轻量级扩散层,分别是基于Feistel结构构造面向软件实现的扩散层和基于LFSR构造面向硬件实现的扩散层。利用三轮Feistel结构,轮函数采用基于循环移位和异或的线性变换,构造出作用在8个4 bit和8 bit S盒上分支数为7的轻量级对合扩散层。基于LFSR构造出作用在4个4 bit和8 bit S盒上的次最优扩散层和作用在8个4 bit和8 bit S盒上分支数为7的扩散层。另外,利用LFSR构造出了6、7、8维MDBL矩阵以及16、18、32维分支数分别为7、7、12的大维数二进制矩阵。研究结果在分组密码的设计方面具有较高的应用价值。展开更多
基金supported by Balochistan University of Engineering and Technology,Khuzdar,Balochistan,Pakistan.
文摘Medical image super-resolution is a fundamental challenge due to absorption and scattering in tissues.These challenges are increasing the interest in the quality of medical images.Recent research has proven that the rapid progress in convolutional neural networks(CNNs)has achieved superior performance in the area of medical image super-resolution.However,the traditional CNN approaches use interpolation techniques as a preprocessing stage to enlarge low-resolution magnetic resonance(MR)images,adding extra noise in the models and more memory consumption.Furthermore,conventional deep CNN approaches used layers in series-wise connection to create the deeper mode,because this later end layer cannot receive complete information and work as a dead layer.In this paper,we propose Inception-ResNet-based Network for MRI Image Super-Resolution known as IRMRIS.In our proposed approach,a bicubic interpolation is replaced with a deconvolution layer to learn the upsampling filters.Furthermore,a residual skip connection with the Inception block is used to reconstruct a high-resolution output image from a low-quality input image.Quantitative and qualitative evaluations of the proposed method are supported through extensive experiments in reconstructing sharper and clean texture details as compared to the state-of-the-art methods.
文摘This paper introduces the process of making 3D vector scenograph of an ancient building with large quantities of data with the aid of AutoCAD,which displays the effect of scenery drawings.The vital skills and technique involved are illustrated through the example of Pagoda of Thousands of Buddha in Chi Lin Nunnery in HongKong.This construction was started in 1996 and finished in 1999 with the concrete structure internal and wood external,imitating the style of buildings in Tang Dynasty.Thus,3D vector scenograph become available to users.
基金financially supported by the Hong Kong Polytechnic University(Grant 1-ZE83,Area of Excellence Project 1ZE30)。
文摘Rechargeable aqueous Zn-ion batteries (ZIBs) have attracted great attention due to their costeffectiveness,high safety,and environmental friendliness.However,some issues associated with poor structural instability of cathode materials and fast self-discharge hinder the further development of ZIBs.Herein,a new configuration is introduced by placing a reduced graphene oxide film as a block layer between the separator and the V2O5·nH2O cathode.This layer prevents the free diffusion of dissolved active materials to the anode and facilitates the transport of Zn ion and electrons,largely improving the cyclic stability and alleviating the self-discharge.Accordingly,the optimized battery delivers a remarkable capacity of 191 mAh g^-1 after 500 cycles at 2 A g^-1.Moreover,a high capacity of 106 mAh g^-1 is achieved after 100 cycles at-20℃.The strategy proposed is expected to be applicable to other electrode systems,thus offering a new approach to circumvent the critical challenges facing aqueous batteries.
文摘以分组密码扩散层为研究对象,根据轻量级分组密码的特点,基于2种密码结构构造轻量级扩散层,分别是基于Feistel结构构造面向软件实现的扩散层和基于LFSR构造面向硬件实现的扩散层。利用三轮Feistel结构,轮函数采用基于循环移位和异或的线性变换,构造出作用在8个4 bit和8 bit S盒上分支数为7的轻量级对合扩散层。基于LFSR构造出作用在4个4 bit和8 bit S盒上的次最优扩散层和作用在8个4 bit和8 bit S盒上分支数为7的扩散层。另外,利用LFSR构造出了6、7、8维MDBL矩阵以及16、18、32维分支数分别为7、7、12的大维数二进制矩阵。研究结果在分组密码的设计方面具有较高的应用价值。
