[HTML][HTML] Machine learning for membrane design and discovery
Membrane technologies are becoming increasingly versatile and helpful today for
sustainable development. Machine Learning (ML), an essential branch of artificial …
sustainable development. Machine Learning (ML), an essential branch of artificial …
Current approaches for choosing feature selection and learning algorithms in quantitative structure–activity relationships (QSAR)
PM Khan, K Roy - Expert opinion on drug discovery, 2018 - Taylor & Francis
Introduction: Quantitative structure-activity/property relationships (QSAR/QSPR) are
statistical models which quantitatively correlate quantitative chemical structure information …
statistical models which quantitatively correlate quantitative chemical structure information …
Single-cell map of diverse immune phenotypes in the breast tumor microenvironment
E Azizi, AJ Carr, G Plitas, AE Cornish, C Konopacki… - Cell, 2018 - cell.com
Knowledge of immune cell phenotypes in the tumor microenvironment is essential for
understanding mechanisms of cancer progression and immunotherapy response. We …
understanding mechanisms of cancer progression and immunotherapy response. We …
Regenerative lineages and immune-mediated pruning in lung cancer metastasis
Developmental processes underlying normal tissue regeneration have been implicated in
cancer, but the degree of their enactment during tumor progression and under the selective …
cancer, but the degree of their enactment during tumor progression and under the selective …
A two-layer dimension reduction and two-tier classification model for anomaly-based intrusion detection in IoT backbone networks
With increasing reliance on Internet of Things (IoT) devices and services, the capability to
detect intrusions and malicious activities within IoT networks is critical for resilience of the …
detect intrusions and malicious activities within IoT networks is critical for resilience of the …
A novel dynamic PCA algorithm for dynamic data modeling and process monitoring
Principal component analysis (PCA) has been widely applied for data modeling and process
monitoring. However, it is not appropriate to directly apply PCA to data from a dynamic …
monitoring. However, it is not appropriate to directly apply PCA to data from a dynamic …
A comparison study of basic data-driven fault diagnosis and process monitoring methods on the benchmark Tennessee Eastman process
This paper provides a comparison study on the basic data-driven methods for process
monitoring and fault diagnosis (PM–FD). Based on the review of these methods and their …
monitoring and fault diagnosis (PM–FD). Based on the review of these methods and their …
AI applications through the whole life cycle of material discovery
We provide a review of machine learning (ML) tools for material discovery and sophisticated
applications of different ML strategies. Although there have been a few published reviews on …
applications of different ML strategies. Although there have been a few published reviews on …
In-process monitoring of selective laser melting: spatial detection of defects via image data analysis
M Grasso, V Laguzza… - Journal of …, 2017 - asmedigitalcollection.asme.org
Selective laser melting (SLM) has been attracting a growing interest in different industrial
sectors as it is one of the key technologies for metal additive manufacturing (AM). Despite …
sectors as it is one of the key technologies for metal additive manufacturing (AM). Despite …
[图书][B] Fault detection and diagnosis in industrial systems
Early and accurate fault detection and diagnosis for modern manufacturing processes can
minimise downtime, increase the safety of plant operations, and reduce costs. Such process …
minimise downtime, increase the safety of plant operations, and reduce costs. Such process …