Stochastic Mutual Information Gradient Estimation for Dimensionality Reduction Networks [0.03%]
基于随机互信息梯度估计的降维网络
Ozan Özdenizci,Deniz Erdoğmuş
Ozan Özdenizci
Feature ranking and selection is a widely used approach in various applications of supervised dimensionality reduction in discriminative machine learning. Nevertheless there exists significant evidence on feature ranking and selection algor...
Inferring statistical trends of the COVID19 pandemic from current data. Where probability meets fuzziness [0.03%]
从当前数据推断COVID19大流行的趋势。概率与模糊性的交汇点
Bruno Apolloni
Bruno Apolloni
We introduce unprecedented tools to infer approximate evolution features of the COVID19 outbreak when these features are altered by containment measures. In this framework we present: (1) a basic tool to deal with samples that are both trun...
A novel framework of collaborative early warning for COVID-19 based on blockchain and smart contracts [0.03%]
基于区块链和智能合约的协作型新冠早期预警框架研究
Liwei Ouyang,Yong Yuan,Yumeng Cao et al.
Liwei Ouyang et al.
Early warning is a vital component of emergency response systems for infectious diseases. However, most early warning systems are centralized and isolated, thus there are potential risks of single evidence bias and decision-making errors. I...
CoV2-Detect-Net: Design of COVID-19 prediction model based on hybrid DE-PSO with SVM using chest X-ray images [0.03%]
基于混合DE-PSO和支持向量机的Covid-19预测模型CoV2-Detect-Net设计及胸片图像分析研究
Abhishek Dixit,Ashish Mani,Rohit Bansal
Abhishek Dixit
For Covid-19 suspected cases, it is critical to diagnose them accurately and rapidly so that they can be isolated and provided with required medical care. A self-learning automation model will be helpful to diagnose the COVID-19 suspected i...
An investigation of testing capacity for evaluating and modeling the spread of coronavirus disease [0.03%]
评估和模拟新型冠状病毒病传播的检测能力调查研究
Choujun Zhan,Jiaqi Chen,Haijun Zhang
Choujun Zhan
Despite the consistent recommendation to scale-up the testing of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), comprehensive analysis on determining the desirable testing capacity (TC) is limited. This study aims to investig...
Attention enhanced long short-term memory network with multi-source heterogeneous information fusion: An application to BGI Genomics [0.03%]
基于多源异构信息融合的注意力增强长短时记忆网络:以贝瑞基因为例的应用研究
Qun Zhang,Lijun Yang,Feng Zhou
Qun Zhang
The recent availability of enormous amounts of both data and computing power has created new opportunities for predictive modeling. This paper compiles an analytical framework based on multiple sources of data including daily trading data, ...
A new approach for classifying coronavirus COVID-19 based on its manifestation on chest X-rays using texture features and neural networks [0.03%]
基于纹理特征和神经网络的胸部X射线冠状病毒COVID-19分类的新方法
Sergio Varela-Santos,Patricia Melin
Sergio Varela-Santos
Since the recent challenge that humanity is facing against COVID-19, several initiatives have been put forward with the goal of creating measures to help control the spread of the pandemic. In this paper we present a series of experiments u...
An intelligent tutoring system for supporting active learning: A case study on predictive parsing learning [0.03%]
支持主动学习的智能教学系统：一种预测语法分析案例研究
J J Castro-Schez,C Glez-Morcillo,J Albusac et al.
J J Castro-Schez et al.
The way in which people learn and institutions teach is changing due to the ever-increasing impact of technology. People access the Internet anywhere, anytime and request online training. This has brought about the creation of numerous onli...
Consensus of large-scale group decision making in social network: the minimum cost model based on robust optimization [0.03%]
社会网络中大规模群体决策的共识:基于鲁棒优化的最小成本模型
Yanling Lu,Yejun Xu,Enrique Herrera-Viedma et al.
Yanling Lu et al.
Recently, large-scale group decision making (LSGDM) in social network comes into being. In the practical consensus of LSGDM, the unit adjustment cost of experts is difficult to obtain and may be uncertain. Therefore, the purpose of this pap...
DNA sequence reconstruction based on innovated hybridization technique of probabilistic cellular automata and particle swarm optimization [0.03%]
基于概率细胞自动机和粒子群优化的创新杂交技术的DNA序列重构
Wesam M Elsayed,Mohammed Elmogy,B S El-Desouky
Wesam M Elsayed
DNA sequence reconstruction is a challenging research problem in the computational biology field. The evolution of the DNA is too complex to be characterized by a few parameters. Therefore, there is a need for a modeling approach for analyz...