COVID-19 comes from a large family of viruses identied in 1965;to date,seven groups have been recorded which have been found to affect humans.In the healthcare industry,there is much evidence that Al or machine learni...COVID-19 comes from a large family of viruses identied in 1965;to date,seven groups have been recorded which have been found to affect humans.In the healthcare industry,there is much evidence that Al or machine learning algorithms can provide effective models that solve problems in order to predict conrmed cases,recovered cases,and deaths.Many researchers and scientists in the eld of machine learning are also involved in solving this dilemma,seeking to understand the patterns and characteristics of virus attacks,so scientists may make the right decisions and take specic actions.Furthermore,many models have been considered to predict the Coronavirus outbreak,such as the retro prediction model,pandemic Kaplan’s model,and the neural forecasting model.Other research has used the time series-dependent face book prophet model for COVID-19 prediction in India’s various countries.Thus,we proposed a prediction and analysis model to predict COVID-19 in Saudi Arabia.The time series dependent face book prophet model is used to t the data and provide future predictions.This study aimed to determine the pandemic prediction of COVID-19 in Saudi Arabia,using the Time Series Analysis to observe and predict the coronavirus pandemic’s spread daily or weekly.We found that the proposed model has a low ability to forecast the recovered cases of the COVID-19 dataset.In contrast,the proposed model of death cases has a high ability to forecast the COVID-19 dataset.Finally,obtaining more data could empower the model for further validation.展开更多
The appearance of a face is severely altered by illumination conditions that makes automatic face recognition a challenging task. In this paper we propose a Gaussian Mixture Models (GMM)-based human face identificatio...The appearance of a face is severely altered by illumination conditions that makes automatic face recognition a challenging task. In this paper we propose a Gaussian Mixture Models (GMM)-based human face identification technique built in the Fourier or frequency domain that is robust to illumination changes and does not require “illumination normalization” (removal of illumination effects) prior to application unlike many existing methods. The importance of the Fourier domain phase in human face identification is a well-established fact in signal processing. A maximum a posteriori (or, MAP) estimate based on the posterior likelihood is used to perform identification, achieving misclassification error rates as low as 2% on a database that contains images of 65 individuals under 21 different illumination conditions. Furthermore, a misclassification rate of 3.5% is observed on the Yale database with 10 people and 64 different illumination conditions. Both these sets of results are significantly better than those obtained from traditional PCA and LDA classifiers. Statistical analysis pertaining to model selection is also presented.展开更多
On the basis of the assumption that the human face belongs to a linear class, a multiple-deformation model is proposed to recover face shape from a few points on a single 2D image. Compared to the conventional methods...On the basis of the assumption that the human face belongs to a linear class, a multiple-deformation model is proposed to recover face shape from a few points on a single 2D image. Compared to the conventional methods, this study has the following advantages. First, the proposed modified 3D sparse deforming model is a noniterative approach that can compute global translation efficiently and accurately. Subsequently, the overfitting problem can be alleviated based on the proposed multiple deformation model. Finally, by keeping the main features, the texture generated is realistic. The comparison results show that this novel method outperforms the existing methods by using ground truth data and that realistic 3D faces can be recovered efficiently from a single photograph.展开更多
A combined method of discrete event and agent based modelling has been applied to the computer modelling and simulation of the tensile strength of one-dimensional fibrous materials (ODFM). This combined method is base...A combined method of discrete event and agent based modelling has been applied to the computer modelling and simulation of the tensile strength of one-dimensional fibrous materials (ODFM). This combined method is based on the concept of discrete event simulation as being applied to the modeling of the structure of the fiber flow and on the concept of agent based modelling for modelling and simulation of the fiber interaction within the structure of the fibrous material. Frictional and traction forces arise as the result of this fiber interaction. A model of the ODFM tensile strength, which is based on the slippage effect, is created and studied in this research. Only frictional and traction forces determine the tensile strength in this kind of the model. The article examines the validation problem of the slippage effect based tensile strength model and questions regarding the strength potential estimation through variation in the parameters of the model.展开更多
A simplified physically-based model was developed to simulate the breaching process of the Gouhou concrete-faced rockfill dam （CFRD）, which is the only breach case of a high CFRD in the world. Considering the dam he...A simplified physically-based model was developed to simulate the breaching process of the Gouhou concrete-faced rockfill dam （CFRD）, which is the only breach case of a high CFRD in the world. Considering the dam height, a hydraulic method was chosen to simulate the initial scour position on the downstream slope, with the steepening of the downstream slope taken into account; a headcut erosion formula was adopted to simulate the backward erosion as well. The moment equilibrium method was utilized to calculate the ultimate length of a concrete slab under its self-weight and water loads. The calculated results of the Gouhou CFRD breach case show that the proposed model provides reasonable peak breach flow, final breach width, and failure time, with relative errors less than 15% as compared with the measured data. Sensitivity studies show that the outputs of the proposed model are more or less sensitive to different parameters. Three typical parametric models were compared with the proposed model, and the comparison demonstrates that the proposed physically-based breach model performs better and provides more detailed results than the parametric models.展开更多
A dislocation interaction model has been proposed for cyclic deformation of fcc crystals.Ac- cording to this model,cyclic stress-strain responses and saturation dislocation structures of a crystal are associated with ...A dislocation interaction model has been proposed for cyclic deformation of fcc crystals.Ac- cording to this model,cyclic stress-strain responses and saturation dislocation structures of a crystal are associated with the modes and intensities of dislocation interactions between slip systems active in the crystal; and,hence,may be predicted by the location of its tensile axis in the crystallographic triangle.This model has successfully explained the different behaviours of double-slip crystals and multi-slip behaviours of some crystals with orientations usually con- sidered as single-slip ones.展开更多
This research focused on the three-dimensional(3 D) seepage field simulation of a high concrete-faced rockfill dam(CFRD) under complex hydraulic conditions. A generalized equivalent continuum model of fractured rock m...This research focused on the three-dimensional(3 D) seepage field simulation of a high concrete-faced rockfill dam(CFRD) under complex hydraulic conditions. A generalized equivalent continuum model of fractured rock mass was used for equivalent continuous seepage field analysis based on the improved node virtual flow method. Using a high CFRD as an example, the generalized equivalent continuum range was determined, and a finite element model was established based on the terrain and geological conditions, as well as structural face characteristics of the dam area. The equivalent seepage coefficients of different material zones or positions in the dam foundation were calculated with the Snow model or inverse analysis. Then, the 3 D seepage field in the dam area was calculated under the normal water storage conditions, and the corresponding water head distribution, seepage flow, seepage gradient, and seepage characteristics in the dam area were analyzed. The results show that the generalized equivalent continuum model can effectively simulate overall seepage patterns of the CFRD under complex hydraulic conditions and provide a reference for seepage analysis of similar CFRDs.展开更多
A new modified conductivity model was established to predict the shear yield stress of electrorheological fluids (ERF). By using a cell equivalent method, the present model can deal with the face-center square structu...A new modified conductivity model was established to predict the shear yield stress of electrorheological fluids (ERF). By using a cell equivalent method, the present model can deal with the face-center square structure of ERF. Combining the scheme of the classical conductivity model for the single-chain structure, a new formula for the prediction of the shear yield stress of ERF was set up. The influences of the separation distance of the particles, the volume fraction of the particles and the applied electric field on the shear yield stress were investigated.展开更多
为了解决传统人脸识别数据集构建中手工标注繁琐、低分辨率图像影响标注准确率等问题的问题,提出一种基于监控视频数据的特定人群人脸数据集自动化构建方法(constructing a facial dataset for a targeted group,CFD-TG)。该方法利用相...为了解决传统人脸识别数据集构建中手工标注繁琐、低分辨率图像影响标注准确率等问题的问题,提出一种基于监控视频数据的特定人群人脸数据集自动化构建方法(constructing a facial dataset for a targeted group,CFD-TG)。该方法利用相邻帧的人脸偏移量和相似度进行分组,并融合标准库进行分组标注和数据增强。实验结果表明,该方法所构数据集的调整兰德系数(ARI)与标准化互信息(NMI)比使用人脸聚类方法分别高出0.189、0.08;并将其在人脸识别模型FaceNet、ArcFace与AdaFace上进行了验证,基于特定人群人脸数据集的微调模型相较与原预训练模型识别准确率分别提升了0.4431、0.5912、0.1288。展开更多
如今,区块链技术被应用到包含电子证照、人脸图像等政府数据共享领域,但当前的大型区块链系统普遍面临低带宽和高存储成本的问题.本文提出了一种适用于政务区块链的跨模态人脸生成模型,将人脸图像转换为文本模态存储在链上,用户可使用...如今,区块链技术被应用到包含电子证照、人脸图像等政府数据共享领域,但当前的大型区块链系统普遍面临低带宽和高存储成本的问题.本文提出了一种适用于政务区块链的跨模态人脸生成模型,将人脸图像转换为文本模态存储在链上,用户可使用文本与掩膜生成指定人的人脸图像.首先利用多任务学习方法训练基于ResNet-18网络结构的人脸分类器,将人脸图像转换为身份代号文本存储在链上.然后设计了区域感知码本和基于Transformer结构的混合专家采样器,采样器采用扩散模型的方法从码本中采样索引,采样结果由一个可学习的解码器转换成细粒度的人脸图像.在进行数据增强后的Casia Face V5数据集上的实验表明,模型在人脸分类任务中准确率可达95%以上,压缩效果达到了传统图像压缩方法1/10000的持久化时间与1/200的文件大小,与其他先进人脸图像生成方法相比,此模型可以可控地生成高保真度的指定人的人脸图像,并以1/20的参数量达到与大型预训练模型相近的人脸生成效果.展开更多
文摘COVID-19 comes from a large family of viruses identied in 1965;to date,seven groups have been recorded which have been found to affect humans.In the healthcare industry,there is much evidence that Al or machine learning algorithms can provide effective models that solve problems in order to predict conrmed cases,recovered cases,and deaths.Many researchers and scientists in the eld of machine learning are also involved in solving this dilemma,seeking to understand the patterns and characteristics of virus attacks,so scientists may make the right decisions and take specic actions.Furthermore,many models have been considered to predict the Coronavirus outbreak,such as the retro prediction model,pandemic Kaplan’s model,and the neural forecasting model.Other research has used the time series-dependent face book prophet model for COVID-19 prediction in India’s various countries.Thus,we proposed a prediction and analysis model to predict COVID-19 in Saudi Arabia.The time series dependent face book prophet model is used to t the data and provide future predictions.This study aimed to determine the pandemic prediction of COVID-19 in Saudi Arabia,using the Time Series Analysis to observe and predict the coronavirus pandemic’s spread daily or weekly.We found that the proposed model has a low ability to forecast the recovered cases of the COVID-19 dataset.In contrast,the proposed model of death cases has a high ability to forecast the COVID-19 dataset.Finally,obtaining more data could empower the model for further validation.
文摘The appearance of a face is severely altered by illumination conditions that makes automatic face recognition a challenging task. In this paper we propose a Gaussian Mixture Models (GMM)-based human face identification technique built in the Fourier or frequency domain that is robust to illumination changes and does not require “illumination normalization” (removal of illumination effects) prior to application unlike many existing methods. The importance of the Fourier domain phase in human face identification is a well-established fact in signal processing. A maximum a posteriori (or, MAP) estimate based on the posterior likelihood is used to perform identification, achieving misclassification error rates as low as 2% on a database that contains images of 65 individuals under 21 different illumination conditions. Furthermore, a misclassification rate of 3.5% is observed on the Yale database with 10 people and 64 different illumination conditions. Both these sets of results are significantly better than those obtained from traditional PCA and LDA classifiers. Statistical analysis pertaining to model selection is also presented.
基金the Program for New Century Excellent Talents in University（NCET） The National Natural Science Foundation of China+1 种基金Beijing Natural Science Foundation ProgramBeijing Science and Educational Committee Program.
文摘On the basis of the assumption that the human face belongs to a linear class, a multiple-deformation model is proposed to recover face shape from a few points on a single 2D image. Compared to the conventional methods, this study has the following advantages. First, the proposed modified 3D sparse deforming model is a noniterative approach that can compute global translation efficiently and accurately. Subsequently, the overfitting problem can be alleviated based on the proposed multiple deformation model. Finally, by keeping the main features, the texture generated is realistic. The comparison results show that this novel method outperforms the existing methods by using ground truth data and that realistic 3D faces can be recovered efficiently from a single photograph.
文摘A combined method of discrete event and agent based modelling has been applied to the computer modelling and simulation of the tensile strength of one-dimensional fibrous materials (ODFM). This combined method is based on the concept of discrete event simulation as being applied to the modeling of the structure of the fiber flow and on the concept of agent based modelling for modelling and simulation of the fiber interaction within the structure of the fibrous material. Frictional and traction forces arise as the result of this fiber interaction. A model of the ODFM tensile strength, which is based on the slippage effect, is created and studied in this research. Only frictional and traction forces determine the tensile strength in this kind of the model. The article examines the validation problem of the slippage effect based tensile strength model and questions regarding the strength potential estimation through variation in the parameters of the model.
基金supported by the National Natural Science Foundation of China(Grants No.51779153,51539006,and 51509156)the Natural Science Foundation of Jiangsu Province(Grant No.BK20161121)
文摘A simplified physically-based model was developed to simulate the breaching process of the Gouhou concrete-faced rockfill dam （CFRD）, which is the only breach case of a high CFRD in the world. Considering the dam height, a hydraulic method was chosen to simulate the initial scour position on the downstream slope, with the steepening of the downstream slope taken into account; a headcut erosion formula was adopted to simulate the backward erosion as well. The moment equilibrium method was utilized to calculate the ultimate length of a concrete slab under its self-weight and water loads. The calculated results of the Gouhou CFRD breach case show that the proposed model provides reasonable peak breach flow, final breach width, and failure time, with relative errors less than 15% as compared with the measured data. Sensitivity studies show that the outputs of the proposed model are more or less sensitive to different parameters. Three typical parametric models were compared with the proposed model, and the comparison demonstrates that the proposed physically-based breach model performs better and provides more detailed results than the parametric models.
文摘A dislocation interaction model has been proposed for cyclic deformation of fcc crystals.Ac- cording to this model,cyclic stress-strain responses and saturation dislocation structures of a crystal are associated with the modes and intensities of dislocation interactions between slip systems active in the crystal; and,hence,may be predicted by the location of its tensile axis in the crystallographic triangle.This model has successfully explained the different behaviours of double-slip crystals and multi-slip behaviours of some crystals with orientations usually con- sidered as single-slip ones.
基金supported by the National Natural Science Youth Foundation of China(Grant No.51309101)the Henan Province Major Scientific and Technological Projects(Grant No.172102210372)the Cooperative Project of Production,Teaching and Research in Henan Province(Grant No.18210700031)
文摘This research focused on the three-dimensional(3 D) seepage field simulation of a high concrete-faced rockfill dam(CFRD) under complex hydraulic conditions. A generalized equivalent continuum model of fractured rock mass was used for equivalent continuous seepage field analysis based on the improved node virtual flow method. Using a high CFRD as an example, the generalized equivalent continuum range was determined, and a finite element model was established based on the terrain and geological conditions, as well as structural face characteristics of the dam area. The equivalent seepage coefficients of different material zones or positions in the dam foundation were calculated with the Snow model or inverse analysis. Then, the 3 D seepage field in the dam area was calculated under the normal water storage conditions, and the corresponding water head distribution, seepage flow, seepage gradient, and seepage characteristics in the dam area were analyzed. The results show that the generalized equivalent continuum model can effectively simulate overall seepage patterns of the CFRD under complex hydraulic conditions and provide a reference for seepage analysis of similar CFRDs.
文摘A new modified conductivity model was established to predict the shear yield stress of electrorheological fluids (ERF). By using a cell equivalent method, the present model can deal with the face-center square structure of ERF. Combining the scheme of the classical conductivity model for the single-chain structure, a new formula for the prediction of the shear yield stress of ERF was set up. The influences of the separation distance of the particles, the volume fraction of the particles and the applied electric field on the shear yield stress were investigated.
文摘为了解决传统人脸识别数据集构建中手工标注繁琐、低分辨率图像影响标注准确率等问题的问题,提出一种基于监控视频数据的特定人群人脸数据集自动化构建方法(constructing a facial dataset for a targeted group,CFD-TG)。该方法利用相邻帧的人脸偏移量和相似度进行分组,并融合标准库进行分组标注和数据增强。实验结果表明,该方法所构数据集的调整兰德系数(ARI)与标准化互信息(NMI)比使用人脸聚类方法分别高出0.189、0.08;并将其在人脸识别模型FaceNet、ArcFace与AdaFace上进行了验证,基于特定人群人脸数据集的微调模型相较与原预训练模型识别准确率分别提升了0.4431、0.5912、0.1288。
文摘如今,区块链技术被应用到包含电子证照、人脸图像等政府数据共享领域,但当前的大型区块链系统普遍面临低带宽和高存储成本的问题.本文提出了一种适用于政务区块链的跨模态人脸生成模型,将人脸图像转换为文本模态存储在链上,用户可使用文本与掩膜生成指定人的人脸图像.首先利用多任务学习方法训练基于ResNet-18网络结构的人脸分类器,将人脸图像转换为身份代号文本存储在链上.然后设计了区域感知码本和基于Transformer结构的混合专家采样器,采样器采用扩散模型的方法从码本中采样索引,采样结果由一个可学习的解码器转换成细粒度的人脸图像.在进行数据增强后的Casia Face V5数据集上的实验表明,模型在人脸分类任务中准确率可达95%以上,压缩效果达到了传统图像压缩方法1/10000的持久化时间与1/200的文件大小,与其他先进人脸图像生成方法相比,此模型可以可控地生成高保真度的指定人的人脸图像,并以1/20的参数量达到与大型预训练模型相近的人脸生成效果.
