Combustion machine learning: Principles, progress and prospects
Progress in combustion science and engineering has led to the generation of large amounts
of data from large-scale simulations, high-resolution experiments, and sensors. This corpus …
of data from large-scale simulations, high-resolution experiments, and sensors. This corpus …
Physical principles of brain–computer interfaces and their applications for rehabilitation, robotics and control of human brain states
Brain–computer interfaces (BCIs) development is closely related to physics. In this paper, we
review the physical principles of BCIs, and underlying novel approaches for registration …
review the physical principles of BCIs, and underlying novel approaches for registration …
An astronomically dated record of Earth's climate and its predictability over the last 66 million years
Much of our understanding of Earth's past climate comes from the measurement of oxygen
and carbon isotope variations in deep-sea benthic foraminifera. Yet, long intervals in …
and carbon isotope variations in deep-sea benthic foraminifera. Yet, long intervals in …
Complex network approaches to nonlinear time series analysis
In the last decade, there has been a growing body of literature addressing the utilization of
complex network methods for the characterization of dynamical systems based on time …
complex network methods for the characterization of dynamical systems based on time …
Global droughts connected by linkages between drought hubs
Quantifying the spatial and interconnected structure of regional to continental scale droughts
is one of the unsolved global hydrology problems, which is important for understanding the …
is one of the unsolved global hydrology problems, which is important for understanding the …
Classification of time-series images using deep convolutional neural networks
Convolutional Neural Networks (CNN) has achieved a great success in image recognition
task by automatically learning a hierarchical feature representation from raw data. While the …
task by automatically learning a hierarchical feature representation from raw data. While the …
EEG analytics for early detection of autism spectrum disorder: a data-driven approach
Autism spectrum disorder (ASD) is a complex and heterogeneous disorder, diagnosed on
the basis of behavioral symptoms during the second year of life or later. Finding scalable …
the basis of behavioral symptoms during the second year of life or later. Finding scalable …
[HTML][HTML] Surrogate data for hypothesis testing of physical systems
G Lancaster, D Iatsenko, A Pidde, V Ticcinelli… - Physics Reports, 2018 - Elsevier
The availability of time series of the evolution of the properties of physical systems is
increasing, stimulating the development of many novel methods for the extraction of …
increasing, stimulating the development of many novel methods for the extraction of …
ECG arrhythmia classification by using a recurrence plot and convolutional neural network
BM Mathunjwa, YT Lin, CH Lin, MF Abbod… - … Signal Processing and …, 2021 - Elsevier
Cardiovascular diseases affect approximately 50 million people worldwide; thus, heart
disease prevention is one of the most important tasks of any health care system. Despite the …
disease prevention is one of the most important tasks of any health care system. Despite the …
Automated detection of schizophrenia using nonlinear signal processing methods
Examination of the brain's condition with the Electroencephalogram (EEG) can be helpful to
predict abnormality and cerebral activities. The purpose of this study was to develop an …
predict abnormality and cerebral activities. The purpose of this study was to develop an …