India perspective: CNN-LSTM hybrid deep learning model-based COVID-19 prediction and current status of medical resource availability [0.03%]
印度视角：基于CNN-LSTM混合深度学习模型的COVID-19预测及当前医疗资源可用性分析
Shwet Ketu,Pramod Kumar Mishra
Shwet Ketu
The epidemic situation may cause severe social and economic impacts on a country. So, there is a need for a trustworthy prediction model that can offer better prediction results. The forecasting result will help in making the prevention pol...
Cognitive computing-based COVID-19 detection on Internet of things-enabled edge computing environment [0.03%]
基于认知计算的物联网边缘计算环境中的COVID-19检测
E Laxmi Lydia,C S S Anupama,A Beno et al.
E Laxmi Lydia et al.
In the current pandemic, smart technologies such as cognitive computing, artificial intelligence, pattern recognition, chatbot, wearables, and blockchain can sufficiently support the collection, analysis, and processing of medical data for ...
A cognitive approach for blockchain-based cryptographic curve hash signature (BC-CCHS) technique to secure healthcare data in Data Lake [0.03%]
基于区块链的加密曲线哈希签名(BC-CCHS)技术在数据湖中保护医疗健康数据的认知方法
Arvind Panwar,Vishal Bhatnagar
Arvind Panwar
In today's digital world, information is exchanged among various sources, and it is expected that each interaction or transaction among the sources must be reliable and secure. In these circumstances, blockchain technology can be applied to...
Consistent posets [0.03%]
一致偏序集
Ivan Chajda,Helmut Länger
Ivan Chajda
We introduce so-called consistent posets which are bounded posets with an antitone involution ' where the lower cones of x , x ' and of y , y ' coincide provided that x, y are different from 0, 1 and, moreover, if x, y are different f...
Improvement on PDP Evaluation Performance Based on Neural Networks and SGDK-means Algorithm [0.03%]
基于神经网络和SGDK-均值算法的PDP评估性能改进
Fan Deng,Zhenhua Yu,Houbing Song et al.
Fan Deng et al.
With the purpose of improving the PDP (policy decision point) evaluation performance, a novel and efficient evaluation engine, namely XDNNEngine, based on neural networks and an SGDK-means (stochastic gradient descent K-means) algorithm is ...
G-optimal designs for hierarchical linear models: an equivalence theorem and a nature-inspired meta-heuristic algorithm [0.03%]
分层线性模型的G-最优设计：一个等价定理和一种自然启发式的元启发算法
Xin Liu,RongXian Yue,Zizhao Zhang et al.
Xin Liu et al.
Hierarchical linear models are widely used in many research disciplines and estimation issues for such models are generally well addressed. Design issues are relatively much less discussed for hierarchical linear models but there is an incr...
Paulo Vitor de Campos Souza,Augusto Junio Guimaraes,Vanessa Souza Araujo et al.
Paulo Vitor de Campos Souza et al.
This paper proposes a Bayesian hybrid approach based on neural networks and fuzzy systems to construct fuzzy rules to assist experts in detecting features and relations regarding the presence of autism in human beings. The model proposed in...
Mahmoud Shaqfa,Katrin Beyer
Mahmoud Shaqfa
In this paper, we propose a simple global optimisation algorithm inspired by Pareto's principle. This algorithm samples most of its solutions within prominent search domains and is equipped with a self-adaptive mechanism to control the dyna...
Filters and congruences in sectionally pseudocomplemented lattices and posets [0.03%]
区间伪补格与偏序集上的滤子和同余关系
Ivan Chajda,Helmut Länger
Ivan Chajda
Together with J. Paseka we introduced so-called sectionally pseudocomplemented lattices and posets and illuminated their role in algebraic constructions. We believe that-similar to relatively pseudocomplemented lattices-these structures can...
Dan Chen
Dan Chen
Uncertain regression model is a powerful analytical tool for exploring the relationship between explanatory variables and response variables. It is assumed that the errors of regression equations are independent. However, in many cases, the...