Methodology-centered review of molecular modeling, simulation, and prediction of SARS-CoV-2
Despite tremendous efforts in the past two years, our understanding of severe acute
respiratory syndrome coronavirus 2 (SARS-CoV-2), virus–host interactions, immune …
respiratory syndrome coronavirus 2 (SARS-CoV-2), virus–host interactions, immune …
EMoSOA: a new evolutionary multi-objective seagull optimization algorithm for global optimization
This study introduces the evolutionary multi-objective version of seagull optimization
algorithm (SOA), entitled Evolutionary Multi-objective Seagull Optimization Algorithm …
algorithm (SOA), entitled Evolutionary Multi-objective Seagull Optimization Algorithm …
Ubiquitous vehicular ad-hoc network computing using deep neural network with iot-based bat agents for traffic management
In this paper, Deep Neural Networks (DNN) with Bat Algorithms (BA) offer a dynamic form of
traffic control in Vehicular Adhoc Networks (VANETs). The former is used to route vehicles …
traffic control in Vehicular Adhoc Networks (VANETs). The former is used to route vehicles …
Detection of COVID-19 cases through X-ray images using hybrid deep neural network
Purpose The latest 2019 coronavirus (COVID-2019), which first appeared in December
2019 in Wuhan's city in China, rapidly spread around the world and became a pandemic. It …
2019 in Wuhan's city in China, rapidly spread around the world and became a pandemic. It …
An integrated model of UTAUT2 to understand consumers' 5G technology acceptance using SEM-ANN approach
It has been a decade since the first extensive study on the internet's adoption and use was
conducted. Circumstances have changed in the last decade internet has become an …
conducted. Circumstances have changed in the last decade internet has become an …
A comprehensive assessment and comparison of tools for HLA class I peptide-binding prediction
Human leukocyte antigen class I (HLA-I) molecules bind intracellular peptides produced by
protein hydrolysis and present them to the T cells for immune recognition and response …
protein hydrolysis and present them to the T cells for immune recognition and response …
BridgeDPI: a novel graph neural network for predicting drug–protein interactions
Motivation Exploring drug–protein interactions (DPIs) provides a rapid and precise approach
to assist in laboratory experiments for discovering new drugs. Network-based methods …
to assist in laboratory experiments for discovering new drugs. Network-based methods …
WITHDRAWN: An approach to minimize the energy consumption during blockchain transaction
Withdrawal Notice WITHDRAWN: An approach to minimize the energy consumption during
blockchain transactionRajit Nair a, Sweta Gupta a, Mukesh Soni b, Piyush Kumar Shukla c …
blockchain transactionRajit Nair a, Sweta Gupta a, Mukesh Soni b, Piyush Kumar Shukla c …
Hybridizing convolutional neural network for classification of lung diseases
Pulmonary disease is widespread worldwide. There is persistent blockage of the lungs,
pneumonia, asthma, TB, etc. It is essential to diagnose the lungs promptly. For this reason …
pneumonia, asthma, TB, etc. It is essential to diagnose the lungs promptly. For this reason …
Probabilistic load forecasting with a non-crossing sparse-group Lasso-quantile regression deep neural network
In this paper, a non-crossing sparse-group Lasso-quantile regression deep neural network
(SGLQRDNN) model is proposed to address electricity load forecasting. Different from the …
(SGLQRDNN) model is proposed to address electricity load forecasting. Different from the …