Prediction and forecasting of worldwide corona virus (COVID-19) outbreak using time series and machine learning [0.03%]
时间序列与机器学习在新型冠状病毒(COVID-19)全球爆发预测和预警中的应用
Priyank Jain,Shriya Sahu
Priyank Jain
How will the newly discovered coronavirus (COVID-19) affect the world and what will be its global impact? For answering this question, we will require a prediction of overall recoveries and fatalities, as well as a reliable prognosis of cor...
Multi-texture features and optimized DeepNet for COVID-19 detection using chest x-ray images [0.03%]
用于胸部X光图像的COVID-19检测的多纹理特征和优化的深度神经网络
Anandbabu Gopatoti,Vijayalakshmi P
Anandbabu Gopatoti
The corona virus disease 2019 (COVID-19) pandemic has a severe influence on population health all over the world. Various methods are developed for detecting the COVID-19, but the process of diagnosing this problem from radiology and radiog...
Jaya-tunicate swarm algorithm based generative adversarial network for COVID-19 prediction with chest computed tomography images [0.03%]
基于结核虫群算法的生成对抗网络用于胸部计算机断层扫描图像的COVID-19预测
Palanivel Rajan Doraiswami,Velliangiri Sarveshwaran,Iwin Thanakumar Joseph Swamidason et al.
Palanivel Rajan Doraiswami et al.
A novel corona virus (COVID-19) has materialized as the respiratory syndrome in recent decades. Chest computed tomography scanning is the significant technology for monitoring and predicting COVID-19. To predict the patients of COVID-19 at ...
Covid-19 detection from radiographs by feature-reinforced ensemble learning [0.03%]
特征增强集成学习在COVID-19检测中的应用
Abdullah Elen
Abdullah Elen
The coronavirus (Covid-19) epidemic continues to have a negative influence on the global population's well-being and health. Scientists in many fields around the world are working non-stop to find a solution to the prevention of this epidem...
Modified unbiased estimators for population variance: An application for COVID-19 deaths in Russia [0.03%]
改进的无偏估计器用于人口方差：俄罗斯COVID-19死亡人数的应用
Hatice Oncel Cekim
Hatice Oncel Cekim
The article deal with the class unbiased forms of the variance estimators using Hartley-Ross type in the simple random sampling. The mean squared error (since it is an unbiased estimator, variance is calculated) of the suggested, up to the ...
Subbiah Sankari,Subramaniam Sankaran Varshini,Savvas Mohamed Aafia Shifana
Subbiah Sankari
Entire world has been affected by Covid-19 pandemic. In fighting against the Covid-19, social distancing and face mask have a paramount role in freezing the spread of the disease. People are asked to limit their interactions with each other...
Enforcing trustworthy cloud SLA with witnesses: A game theory-based model using smart contracts [0.03%]
基于博弈论和智能合约的可信云SLA模型及验证方法研究
Huan Zhou,Xue Ouyang,Jinshu Su et al.
Huan Zhou et al.
There lacks trust between the cloud customer and provider to enforce traditional cloud SLA (Service Level Agreement) where the blockchain technique seems a promising solution. However, current explorations still face challenges to prove tha...
A multi-core ready discrete element method with triangles using dynamically adaptive multiscale grids [0.03%]
一种基于三角形的多核离散单元法及其动态自适应多尺度网格
Konstantinos Krestenitis,Tobias Weinzierl
Konstantinos Krestenitis
The simulation of vast numbers of rigid bodies of non-analytical shapes and of tremendously different sizes that collide with each other is computationally challenging. A bottleneck is the identification of all particle contact points per t...
Combining the advantages of AlexNet convolutional deep neural network optimized with anopheles search algorithm based feature extraction and random forest classifier for COVID-19 classification [0.03%]
基于蚊子搜索算法优化的AlexNet卷积深度神经网络与随机森林分类器结合的优势进行特征提取并用于新冠肺炎分类
Sumaiya Begum Akbar,Kalaiselvi Thanupillai,Suganthi Sundararaj
Sumaiya Begum Akbar
In this article, COVID-19 detection and classification framework based on anopheles search optimized AlexNet convolutional deep neural network for random forest classifier is implemented. Here, the COVID-19 dataset is taken from Joseph Paul...
A novel COVID-19 sentiment analysis in Turkish based on the combination of convolutional neural network and bidirectional long-short term memory on Twitter [0.03%]
一种基于卷积神经网络和双向长短期记忆在Twitter上结合的新颖的土耳其语COVID-19情绪分析方法
Abdullah Talha Kabakus
Abdullah Talha Kabakus
The whole world has been experiencing the COVID-19 pandemic since December 2019. During the pandemic, a new life has been started by necessity where people have extensively used social media to express their feelings, and find information. ...