A mixed integer linear programming model and a basic variable neighbourhood search algorithm for the repatriation scheduling problem [0.03%]
带回归调度问题的混合整数线性规划模型及其基本变量邻域搜索算法
Sameh Al-Shihabi,Nenad Mladenović
Sameh Al-Shihabi
Commercial flights nearly halted due to the COVID-19 pandemic in the second quarter of 2020. Consequently, several countries have had to schedule repatriation flights to return their citizens stranded in other countries. Flight routes and s...
Artificial intelligence-based decision support model for new drug development planning [0.03%]
基于人工智能的新药研发规划决策支持模型
Ye Lim Jung,Hyoung Sun Yoo,JeeNa Hwang
Ye Lim Jung
New drug development guarantees a very high return on success, but the success rate is extremely low. Pharmaceutical companies have attempted to use various strategies to increase the success rate of drug development, but this goal has been...
Puja Gupta,Varsha Sharma,Sunita Varma
Puja Gupta
Face recognition has become a significant challenge today since an increasing number of individuals wear masks to avoid infection with the novel coronavirus or Covid-19. Due to its rapid proliferation, it has garnered growing attention. The...
A novel algorithm for detection of COVID-19 by analysis of chest CT images using Hopfield neural network [0.03%]
基于Hopfield神经网络分析胸部CT图像的COVID-19检测新算法
Saeed Sani,Hossein Ebrahimzadeh Shermeh
Saeed Sani
Background: Widely spread of the COVID-19 virus has put the whole world in jeopardy. At this moment, using new techniques to detect and treat this novel disease is of significance or maybe the first priority of many scien...
Temporal deep learning architecture for prediction of COVID-19 cases in India [0.03%]
印度COVID-19病例预测的时序深度学习模型
Hanuman Verma,Saurav Mandal,Akshansh Gupta
Hanuman Verma
To combat the recent coronavirus disease 2019 (COVID-19), academician and clinician are in search of new approaches to predict the COVID-19 outbreak dynamic trends that may slow down or stop the pandemic. Epidemiological models like Suscept...
Complex features extraction with deep learning model for the detection of COVID19 from CT scan images using ensemble based machine learning approach [0.03%]
基于集成机器学习方法的CT扫描图像COVID19检测的深度学习模型复杂特征提取研究
Md Robiul Islam,Md Nahiduzzaman
Md Robiul Islam
Recently the most infectious disease is the novel Coronavirus disease (COVID 19) creates a devastating effect on public health in more than 200 countries in the world. Since the detection of COVID19 using reverse transcription-polymerase ch...
Prioritizing and queueing the emergency departments' patients using a novel data-driven decision-making methodology, a real case study [0.03%]
基于数据驱动决策的急诊患者优先级排序的新方法及实证研究
Mohammad Alipour-Vaezi,Amir Aghsami,Fariborz Jolai
Mohammad Alipour-Vaezi
One of the principal problems in epidemic disruptions like the COVID-19 pandemic is that the number of patients needing hospitals' emergency departments' services significantly grows. Since COVID-19 is an infectious disease, any aggregation...
Detection of intra-family coronavirus genome sequences through graphical representation and artificial neural network [0.03%]
基于图形表示和人工神经网络的冠状病毒基因组序列的族内检测方法研究
Tirthankar Paul,Seppo Vainio,Juha Roning
Tirthankar Paul
In this study, chaos game representation (CGR) is introduced for investigating the pattern of genome sequences. It is an image representation of the genome for the overall visualization of the sequence. The CGR representation is a mapping t...
Are CDS spreads predictable during the Covid-19 pandemic? Forecasting based on SVM, GMDH, LSTM and Markov switching autoregression [0.03%]
新冠疫情下的CDS利差可预测吗？基于SVM、GMDH、LSTM和马尔科夫切换自回归的预测研究
Darko B Vukovic,Kirill Romanyuk,Sergey Ivashchenko et al.
Darko B Vukovic et al.
This paper investigates the forecasting performance for credit default swap (CDS) spreads by Support Vector Machines (SVM), Group Method of Data Handling (GMDH), Long Short-Term Memory (LSTM) and Markov switching autoregression (MSA) for da...
Efficient and visualizable convolutional neural networks for COVID-19 classification using Chest CT [0.03%]
基于胸部CT的高效且可视化的卷积神经网络在COVID-19分类中的应用
Aksh Garg,Sana Salehi,Marianna La Rocca et al.
Aksh Garg et al.
With coronavirus disease 2019 (COVID-19) cases rising rapidly, deep learning has emerged as a promising diagnosis technique. However, identifying the most accurate models to characterize COVID-19 patients is challenging because comparing re...