Computational intelligence and neuroscience
Nov 28, 2022
The huge number of network traffic data, the abundance of available network features, and the diversity of cyber-attack patterns mean that intrusion detection remains difficult even though many earlier efforts have succeeded in building the Internet ...
This paper proposes an automatic air-to-ground (A2G) channel model selection method based on machine learning (ML) using digital surface model (DSM) terrain data. In order to verify whether a communication network for a new non-terrestrial user servi...
Cryptojacking or illegal mining is a form of malware that hides in the victim's computer and takes the computational resources to extract cryptocurrencies in favor of the attacker. It generates significant computational consumption, reducing the comp...
Connectivity and automation have expanded with the development of autonomous vehicle technology. One of several automotive serial protocols that can be used in a wide range of vehicles is the controller area network (CAN). The growing functionality a...
Colloidal particles can attach to surfaces during transport, but the attachment depends on particle size, hydrodynamics, solid and water chemistry, and particulate matter. The attachment is quantified in filtration theory by measuring attachment or s...
International journal of medical informatics
Nov 25, 2022
BACKGROUND: The progress of digital transformation in clinical practice opens the door to transforming the current clinical line for liver disease diagnosis from a late-stage diagnosis approach to an early-stage based one. Early diagnosis of liver fi...
BACKGROUND AND OBJECTIVES: We sought to summarize the study design, modelling strategies, and performance measures reported in studies on clinical prediction models developed using machine learning techniques.
Mathematical biosciences and engineering : MBE
Nov 25, 2022
G protein-coupled receptors (GPCRs) have been the targets for more than 40% of the currently approved drugs. Although neural networks can effectively improve the accuracy of prediction with the biological activity, the result is undesirable in the li...
INTRODUCTION: Machine learning algorithms have received increased attention in neurosurgical literature for improved accuracy over traditional predictive methods. In this review, the authors sought to assess current applications of machine learning f...
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